Investigation of Salmonella Enteritidis outbreaks in South Africa using multi-locus variable-number tandem-repeats analysis, 2013-2015.

PubMed

Muvhali, Munyadziwa; Smith, Anthony Marius; Rakgantso, Andronica Moipone; Keddy, Karen Helena

2017-10-02

Salmonella enterica serovar Enteritidis (Salmonella Enteritidis) has become a significant pathogen in South Africa, and the need for improved molecular surveillance of this pathogen has become important. Over the years, multi-locus variable-number tandem-repeats analysis (MLVA) has become a valuable molecular subtyping technique for Salmonella, particularly for highly homogenic serotypes such as Salmonella Enteritidis. This study describes the use of MLVA in the molecular epidemiological investigation of outbreak isolates in South Africa. Between the years 2013 and 2015, the Centre for Enteric Diseases (CED) received 39 Salmonella Enteritidis isolates from seven foodborne illness outbreaks, which occurred in six provinces. MLVA was performed on all isolates. Three MLVA profiles (MLVA profiles 21, 22 and 28) were identified among the 39 isolates. MLVA profile 28 accounted for 77% (30/39) of the isolates. Isolates from a single outbreak were grouped into a single MLVA profile. A minimum spanning tree (MST) created from the MLVA data showed a close relationship between MLVA profiles 21, 22 and 28, with a single VNTR locus difference between them. MLVA has proven to be a reliable method for the molecular epidemiological investigation of Salmonella Enteritidis outbreaks in South Africa. These foodborne outbreaks emphasize the importance of the One Health approach as an essential component for combating the spread of zoonotic pathogens such as Salmonella Enteritidis.

The evaluation and application of multilocus variable number tandem repeat analysis (MLVA) for the molecular epidemiological study of Salmonella enterica subsp. enterica serovar Enteritidis infection.

PubMed

Liu, Yao; Shi, Xiaolu; Li, Yinghui; Chen, Qiongcheng; Jiang, Min; Li, Wanli; Qiu, Yaqun; Lin, Yiman; Jiang, Yixiang; Kan, Biao; Sun, Qun; Hu, Qinghua

2016-01-29

Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is one of the most prevalent Salmonella serotypes that cause gastroenteritis worldwide and the most prevalent serotype causing Salmonella infections in China. A rapid molecular typing method with high throughput and good epidemiological discrimination is urgently needed for detecting the outbreaks and finding the source for effective control of S. Enteritidis infections. In this study, 194 strains which included 47 from six outbreaks that were well-characterized epidemiologically were analyzed with pulse field gel electrophoresis (PFGE) and multilocus variable number tandem repeat analysis (MLVA). Seven VNTR loci published by the US Center for Disease Control and Prevention (CDC) were used to evaluate and develop MLVA scheme for S. Enteritidis molecular subtyping by comparing with PFGE, and then MLVA was applied to the suspected outbreaks detection. All S. Enteritidis isolates were analyzed with MLVA to establish a MLVA database in Shenzhen, Guangdong province, China to facilitate the detection of S. Enteritidis infection clusters. There were 33 MLVA types and 29 PFGE patterns among 147 sporadic isolates. These two measures had Simpson indices of 0.7701 and 0.8043, respectively, which did not differ significantly. Epidemiological concordance was evaluated by typing 47 isolates from six epidemiologically well-characterized outbreaks and it did not differ for PFGE and MLVA. We applied the well established MLVA method to detect two S. Enteritidis foodborne outbreaks and find their sources successfully in 2014. A MLVA database of 491 S. Enteritidis strains isolated from 2004 to 2014 was established for the surveillance of clusters in the future. MLVA typing of S. Enteritidis would be an effective tool for early warning and epidemiological surveillance of S. Enteritidis infections.

Genetic diversity of Brucella ovis isolates from Rio Grande do Sul, Brazil, by MLVA16

PubMed Central

2014-01-01

Background Ovine epididymitis is predominantly associated with Brucella ovis infection. Molecular characterization of Brucella spp. achieved by multi-locus variable number of tandem repeats (VNTR) analyses (MLVA) have proved to be a powerful tool for epidemiological trace-back studies. Thus, the aim of this study was to evaluate the genetic diversity of Brucella ovis isolates from Rio Grande do Sul State, Brazil, by MLVA16. Findings MLVA16 genotyping identified thirteen distinct genotypes and a Hunter-Gaston diversity index of 0.989 among the fourteen B. ovis genotyped strains. All B. ovis MLVA16 genotypes observed in the present study represented non-previously described profiles. Analyses of the eight conserved loci included in panel 1 (MLVA8) showed three different genotypes, two new and one already described for B. ovis isolates. Among ten B. ovis isolates from same herd only two strains had identical pattern, whereas the four isolates with no epidemiologic information exhibited a single MLVA16 pattern each. Analysis of minimal spanning tree, constructed using the fourteen B. ovis strains typed in this study together with all nineteen B. ovis MLVA16 genotypes available in the MLVAbank 2014, revealed the existence of two clearly distinct major clonal complexes. Conclusions In conclusion, the results of the present study showed a high genetic diversity among B. ovis field isolates from Rio Grande do Sul State, Brazil, by MLVA16. PMID:25015223

Genetic diversity of Brucella ovis isolates from Rio Grande do Sul, Brazil, by MLVA16.

PubMed

Dorneles, Elaine M S; Freire, Guilherme N; Dasso, Maurício G; Poester, Fernando P; Lage, Andrey P

2014-07-12

Ovine epididymitis is predominantly associated with Brucella ovis infection. Molecular characterization of Brucella spp. achieved by multi-locus variable number of tandem repeats (VNTR) analyses (MLVA) have proved to be a powerful tool for epidemiological trace-back studies. Thus, the aim of this study was to evaluate the genetic diversity of Brucella ovis isolates from Rio Grande do Sul State, Brazil, by MLVA16. MLVA16 genotyping identified thirteen distinct genotypes and a Hunter-Gaston diversity index of 0.989 among the fourteen B. ovis genotyped strains. All B. ovis MLVA16 genotypes observed in the present study represented non-previously described profiles. Analyses of the eight conserved loci included in panel 1 (MLVA8) showed three different genotypes, two new and one already described for B. ovis isolates. Among ten B. ovis isolates from same herd only two strains had identical pattern, whereas the four isolates with no epidemiologic information exhibited a single MLVA16 pattern each. Analysis of minimal spanning tree, constructed using the fourteen B. ovis strains typed in this study together with all nineteen B. ovis MLVA16 genotypes available in the MLVAbank 2014, revealed the existence of two clearly distinct major clonal complexes. In conclusion, the results of the present study showed a high genetic diversity among B. ovis field isolates from Rio Grande do Sul State, Brazil, by MLVA16.

Lab on a chip genotyping for Brucella spp. based on 15-loci multi locus VNTR analysis.

PubMed

De Santis, Riccardo; Ciammaruconi, Andrea; Faggioni, Giovanni; D'Amelio, Raffaele; Marianelli, Cinzia; Lista, Florigio

2009-04-07

Brucellosis is an important zoonosis caused by the genus Brucella. In addition Brucella represents potential biological warfare agents due to the high contagious rates for humans and animals. Therefore, the strain typing epidemiological tool may be crucial for tracing back source of infection in outbreaks and discriminating naturally occurring outbreaks versus bioterroristic event. A Multiple Locus Variable-number tandem repeats (VNTR) Analysis (MLVA) assay based on 15 polymorphic markers was previously described. The obtained MLVA band profiles may be resolved by techniques ranging from low cost manual agarose gels to the more expensive capillary electrophoresis sequencing. In this paper a rapid, accurate and reproducible system, based on the Lab on a chip technology was set up for Brucella spp. genotyping. Seventeen DNA samples of Brucella strains isolated in Sicily, previously genotyped, and twelve DNA samples, provided by MLVA Brucella VNTR ring trial, were analyzed by MLVA-15 on Agilent 2100. The DNA fragment sizes produced by Agilent, compared with those expected, showed discrepancies; therefore, in order to assign the correct alleles to the Agilent DNA fragment sizes, a conversion table was produced. In order to validate the system twelve unknown DNA samples were analyzed by this method obtaining a full concordance with the VNTR ring trial results. In this paper we described a rapid and specific detection method for the characterization of Brucella isolates. The comparison of the MLVA typing data produced by Agilent system with the data obtained by standard sequencing or ethidium bromide slab gel electrophoresis showed a general concordance of the results. Therefore this platform represents a fair compromise among costs, speed and specificity compared to any conventional molecular typing technique.

Evaluation of Fourier transform infrared (FT-IR) spectroscopy and chemometrics as a rapid approach for sub-typing Escherichia coli O157:H7 isolates.

PubMed

Davis, R; Paoli, G; Mauer, L J

2012-09-01

The importance of tracking outbreaks of foodborne illness and the emergence of new virulent subtypes of foodborne pathogens have created the need for rapid and reliable sub-typing methods for Escherichia coli O157:H7. Fourier transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analyses was used for sub-typing 30 strains of E. coli O157:H7 that had previously been typed by multilocus variable number tandem repeat analysis (MLVA) and pulsed field gel electrophoresis (PFGE). Hierarchical cluster analysis (HCA) and canonical variate analysis (CVA) of the FT-IR spectra resulted in the clustering of the same or similar MLVA types and separation of different MLVA types of E. coli O157:H7. The developed FT-IR method showed better discriminatory power than PFGE in sub-typing E. coli O157:H7. Results also indicated the spectral relatedness between different outbreak strains. However, the grouping of some strains was not in complete agreement with the clustering based on PFGE and MLVA. Additionally, HCA of the spectra differentiated the strains into 30 sub-clusters, indicating the high specificity and suitability of the method for strain level identification. Strains were also classified (97% correct) based on the type of Shiga toxin present using CVA of the spectra. This study demonstrated that FT-IR spectroscopy is suitable for rapid (≤16 h) and economical sub-typing of E. coli O157:H7 with comparable accuracy to MLVA typing. This is the first report of using an FT-IR-based method for sub-typing E. coli O157:H7. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analysis of Salmonella enterica Serovar Typhimurium Variable-Number Tandem-Repeat Data for Public Health Investigation Based on Measured Mutation Rates and Whole-Genome Sequence Comparisons

PubMed Central

Dimovski, Karolina; Cao, Hanwei; Wijburg, Odilia L. C.; Strugnell, Richard A.; Mantena, Radha K.; Whipp, Margaret; Hogg, Geoff

2014-01-01

Variable-number tandem repeats (VNTRs) mutate rapidly and can be useful markers for genotyping. While multilocus VNTR analysis (MLVA) is increasingly used in the detection and investigation of food-borne outbreaks caused by Salmonella enterica serovar Typhimurium (S. Typhimurium) and other bacterial pathogens, MLVA data analysis usually relies on simple clustering approaches that may lead to incorrect interpretations. Here, we estimated the rates of copy number change at each of the five loci commonly used for S. Typhimurium MLVA, during in vitro and in vivo passage. We found that loci STTR5, STTR6, and STTR10 changed during passage but STTR3 and STTR9 did not. Relative rates of change were consistent across in vitro and in vivo growth and could be accurately estimated from diversity measures of natural variation observed during large outbreaks. Using a set of 203 isolates from a series of linked outbreaks and whole-genome sequencing of 12 representative isolates, we assessed the accuracy and utility of several alternative methods for analyzing and interpreting S. Typhimurium MLVA data. We show that eBURST analysis was accurate and informative. For construction of MLVA-based trees, a novel distance metric, based on the geometric model of VNTR evolution coupled with locus-specific weights, performed better than the commonly used simple or categorical distance metrics. The data suggest that, for the purpose of identifying potential transmission clusters for further investigation, isolates whose profiles differ at one of the rapidly changing STTR5, STTR6, and STTR10 loci should be collapsed into the same cluster. PMID:24957617

High throughput MLVA-16 typing for Brucella based on the microfluidics technology

PubMed Central

2011-01-01

Background Brucellosis, a zoonosis caused by the genus Brucella, has been eradicated in Northern Europe, Australia, the USA and Canada, but remains endemic in most areas of the world. The strain and biovar typing of Brucella field samples isolated in outbreaks is useful for tracing back source of infection and may be crucial for discriminating naturally occurring outbreaks versus bioterrorist events, being Brucella a potential biological warfare agent. In the last years MLVA-16 has been described for Brucella spp. genotyping. The MLVA band profiles may be resolved by different techniques i.e. the manual agarose gels, the capillary electrophoresis sequencing systems or the microfluidic Lab-on-Chip electrophoresis. In this paper we described a high throughput system of MLVA-16 typing for Brucella spp. by using of the microfluidics technology. Results The Caliper LabChip 90 equipment was evaluated for MLVA-16 typing of sixty-three Brucella samples. Furthermore, in order to validate the system, DNA samples previously resolved by sequencing system and Agilent technology, were de novo genotyped. The comparison of the MLVA typing data obtained by the Caliper equipment and those previously obtained by the other analysis methods showed a good correlation. However the outputs were not accurate as the Caliper DNA fragment sizes showed discrepancies compared with real data and a conversion table from observed to expected data was created. Conclusion In this paper we described the MLVA-16 using a rapid, sophisticated microfluidics technology for detection of amplification product sizes. The comparison of the MLVA typing data produced by Caliper LabChip 90 system with the data obtained by different techniques showed a general concordance of the results. Furthermore this platform represents a significant improvement in terms of handling, data acquiring, computational efficiency and rapidity, allowing to perform the strain genotyping in a time equal to one sixth respect to other microfluidics systems as e.g. the Agilent 2100 bioanalyzer. Finally, this platform can be considered a valid alternative to standard genotyping techniques, particularly useful dealing with a large number of samples in short time. These data confirmed that this technology represents a significative advancement in high-throughput accurate Brucella genotyping. PMID:21435217

Staphylococcus aureus strains associated with food poisoning outbreaks in France: comparison of different molecular typing methods, including MLVA

PubMed Central

Roussel, Sophie; Felix, Benjamin; Vingadassalon, Noémie; Grout, Joël; Hennekinne, Jacques-Antoine; Guillier, Laurent; Brisabois, Anne; Auvray, Fréderic

2015-01-01

Staphylococcal food poisoning outbreaks (SFPOs) are frequently reported in France. However, most of them remain unconfirmed, highlighting a need for a better characterization of isolated strains. Here we analyzed the genetic diversity of 112 Staphylococcus aureus strains isolated from 76 distinct SFPOs that occurred in France over the last 30 years. We used a recently developed multiple-locus variable-number tandem-repeat analysis (MLVA) protocol and compared this method with pulsed field gel electrophoresis (PFGE), spa-typing and carriage of genes (se genes) coding for 11 staphylococcal enterotoxins (i.e., SEA, SEB, SEC, SED, SEE, SEG, SEH, SEI, SEJ, SEP, SER). The strains known to have an epidemiological association with one another had identical MLVA types, PFGE profiles, spa-types or se gene carriage. MLVA, PFGE and spa-typing divided 103 epidemiologically unrelated strains into 84, 80, and 50 types respectively demonstrating the high genetic diversity of S. aureus strains involved in SFPOs. Each MLVA type shared by more than one strain corresponded to a single spa-type except for one MLVA type represented by four strains that showed two different-but closely related-spa-types. The 87 enterotoxigenic strains were distributed across 68 distinct MLVA types that correlated all with se gene carriage except for four MLVA types. The most frequent se gene detected was sea, followed by seg and sei and the most frequently associated se genes were sea-seh and sea-sed-sej-ser. The discriminatory ability of MLVA was similar to that of PFGE and higher than that of spa-typing. This MLVA protocol was found to be compatible with high throughput analysis, and was also faster and less labor-intensive than PFGE. MLVA holds promise as a suitable method for investigating SFPOs and tracking the source of contamination in food processing facilities in real time. PMID:26441849

Phylogenetic Analysis of Enterohemorrhagic Escherichia coli O157, Germany, 1987–2008

PubMed Central

Jenke, Christian; Harmsen, Dag; Weniger, Thomas; Rothgänger, Jörg; Hyytiä-Trees, Eija; Bielaszewska, Martina; Karch, Helge

2010-01-01

Multilocus variable number tandem repeat analysis (MLVA) is a subtyping technique for characterizing human pathogenic bacteria such as enterohemorrhagic Escherichia coli (EHEC) O157. We determined the phylogeny of 202 epidemiologically unrelated EHEC O157:H7/H– clinical isolates through 8 MLVA loci obtained in Germany during 1987–2008. Biodiversity in the loci ranged from 0.66 to 0.90. Four of 8 loci showed null alleles and a frequency <44.1%. These loci were distributed among 48.5% of all strains. Overall, 141 MLVA profiles were identified. Phylogenetic analysis assigned 67.3% of the strains to 19 MLVA clusters. Specific MLVA profiles with an evolutionary persistence were identified, particularly within sorbitol-fermenting EHEC O157:H–.These pathogens belonged to the same MLVA cluster. Our findings indicate successful persistence of this clone. PMID:20350374

Phylogenetic analysis of enterohemorrhagic Escherichia coli O157, Germany, 1987-2008.

PubMed

Jenke, Christian; Harmsen, Dag; Weniger, Thomas; Rothganger, Jorg; Hyytia-Trees, Eija; Bielaszewska, Martina; Karch, Helge; Mellmann, Alexander

2010-04-01

Multilocus variable number tandem repeat analysis (MLVA) is a subtyping technique for characterizing human pathogenic bacteria such as enterohemorrhagic Escherichia coli (EHEC) O157. We determined the phylogeny of 202 epidemiologically unrelated EHEC O157:H7/H- clinical isolates through 8 MLVA loci obtained in Germany during 1987-2008. Biodiversity in the loci ranged from 0.66 to 0.90. Four of 8 loci showed null alleles and a frequency < or =44.1%. These loci were distributed among 48.5% of all strains. Overall, 141 MLVA profiles were identified. Phylogenetic analysis assigned 67.3% of the strains to 19 MLVA clusters. Specific MLVA profiles with an evolutionary persistence were identified, particularly within sorbitol-fermenting EHEC O157:H-.These pathogens belonged to the same MLVA cluster. Our findings indicate successful persistence of this clone.

Multi-locus variable number tandem repeat analysis of 7th pandemic Vibrio cholerae

PubMed Central

2012-01-01

Background Seven pandemics of cholera have been recorded since 1817, with the current and ongoing pandemic affecting almost every continent. Cholera remains endemic in developing countries and is still a significant public health issue. In this study we use multilocus variable number of tandem repeats (VNTRs) analysis (MLVA) to discriminate between isolates of the 7th pandemic clone of Vibrio cholerae. Results MLVA of six VNTRs selected from previously published data distinguished 66 V. cholerae isolates collected between 1961–1999 into 60 unique MLVA profiles. Only 4 MLVA profiles consisted of more than 2 isolates. The discriminatory power was 0.995. Phylogenetic analysis showed that, except for the closely related profiles, the relationships derived from MLVA profiles were in conflict with that inferred from Single Nucleotide Polymorphism (SNP) typing. The six SNP groups share consensus VNTR patterns and two SNP groups contained isolates which differed by only one VNTR locus. Conclusions MLVA is highly discriminatory in differentiating 7th pandemic V. cholerae isolates and MLVA data was most useful in resolving the genetic relationships among isolates within groups previously defined by SNPs. Thus MLVA is best used in conjunction with SNP typing in order to best determine the evolutionary relationships among the 7th pandemic V. cholerae isolates and for longer term epidemiological typing. PMID:22624829

Multiple Locus Variable-Number Tandem-Repeat and Single-Nucleotide Polymorphism-Based Brucella Typing Reveals Multiple Lineages in Brucella melitensis Currently Endemic in China.

PubMed

Sun, Mingjun; Jing, Zhigang; Di, Dongdong; Yan, Hao; Zhang, Zhicheng; Xu, Quangang; Zhang, Xiyue; Wang, Xun; Ni, Bo; Sun, Xiangxiang; Yan, Chengxu; Yang, Zhen; Tian, Lili; Li, Jinping; Fan, Weixing

2017-01-01

Brucellosis is a worldwide zoonotic disease caused by Brucella spp. In China, brucellosis is recognized as a reemerging disease mainly caused by Brucella melitensis specie. To better understand the currently endemic B. melitensis strains in China, three Brucella genotyping methods were applied to 110 B. melitensis strains obtained in past several years. By MLVA genotyping, five MLVA-8 genotypes were identified, among which genotypes 42 (1-5-3-13-2-2-3-2) was recognized as the predominant genotype, while genotype 63 (1-5-3-13-2-3-3-2) and a novel genotype of 1-5-3-13-2-4-3-2 were second frequently observed. MLVA-16 discerned a total of 57 MLVA-16 genotypes among these Brucella strains, with 41 genotypes being firstly detected and the other 16 genotypes being previously reported. By BruMLSA21 typing, six sequence types (STs) were identified, among them ST8 is the most frequently seen in China while the other five STs were firstly detected and designated as ST137, ST138, ST139, ST140, and ST141 by international multilocus sequence typing database. Whole-genome sequence (WGS)-single-nucleotide polymorphism (SNP)-based typing and phylogenetic analysis resolved Chinese B. melitensis strains into five clusters, reflecting the existence of multiple lineages among these Chinese B. melitensis strains. In phylogeny, Chinese lineages are more closely related to strains collected from East Mediterranean and Middle East countries, such as Turkey, Kuwait, and Iraq. In the next few years, MLVA typing will certainly remain an important epidemiological tool for Brucella infection analysis, as it displays a high discriminatory ability and achieves result largely in agreement with WGS-SNP-based typing. However, WGS-SNP-based typing is found to be the most powerful and reliable method in discerning Brucella strains and will be popular used in the future.

New system for multilocus variable-number tandem-repeat analysis of the enterohemorrhagic Escherichia coli strains belonging to three major serogroups: O157, O26, and O111.

PubMed

Izumiya, Hidemasa; Pei, Yingxin; Terajima, Jun; Ohnishi, Makoto; Hayashi, Tetsuya; Iyoda, Sunao; Watanabe, Haruo

2010-10-01

Enterohemorrhagic Escherichia coli (EHEC), a food- and waterborne pathogen, causes diarrhea, hemorrhagic colitis, and life-threatening HUS. MLVA is a newly developed and widely accepted genotyping tool. An MLVA system for EHEC O157 involving nine genomic loci has already been established. However, the present study revealed that the above-mentioned MLVA system cannot analyze EHEC O26 and O111 isolates-the second and third most dominant EHEC serogroups in Japan, respectively. Therefore, with several modifications to the O157 system and the use of nine additional loci, we developed an expanded MLVA system applicable to EHEC O26, O111, and O157. Our MLVA system had a relatively high resolution power for each of the three serogroups: Simpson's index of diversity was 0.991 (95% CI = 0.989-0.993), 0.988 (95% CI, 0.986-0.990), and 0.986 (95% CI, 0.979-0.993) for O26, O111, and O157, respectively. This system also detected outbreak-related isolates; the isolates collected during each of the 12 O26 and O111 outbreaks formed unique clusters, and most of the repeat copy numbers among the isolates collected during the same outbreak exhibited no or single-locus variations. These results were comparable to those of cluster analyses based on PFGE profiles. Therefore, our system can complement PFGE analysis-the current golden method. Because EHEC strains of three major serogroups can be rapidly analyzed on a single platform with our expanded MLVA system, this system could be widely used in molecular epidemiological studies of EHEC infections. © 2010 The Societies and Blackwell Publishing Asia Pty Ltd.

Multiple-locus variable-number tandem repeat analysis for strain discrimination of non-O157 Shiga toxin-producing Escherichia coli.

PubMed

Timmons, Chris; Trees, Eija; Ribot, Efrain M; Gerner-Smidt, Peter; LaFon, Patti; Im, Sung; Ma, Li Maria

2016-06-01

Non-O157 Shiga toxin-producing Escherichia coli (STEC) are foodborne pathogens of growing concern worldwide that have been associated with several recent multistate and multinational outbreaks of foodborne illness. Rapid and sensitive molecular-based bacterial strain discrimination methods are critical for timely outbreak identification and contaminated food source traceback. One such method, multiple-locus variable-number tandem repeat analysis (MLVA), is being used with increasing frequency in foodborne illness outbreak investigations to augment the current gold standard bacterial subtyping technique, pulsed-field gel electrophoresis (PFGE). The objective of this study was to develop a MLVA assay for intra- and inter-serogroup discrimination of six major non-O157 STEC serogroups-O26, O111, O103, O121, O45, and O145-and perform a preliminary internal validation of the method on a limited number of clinical isolates. The resultant MLVA scheme consists of ten variable number tandem repeat (VNTR) loci amplified in three multiplex PCR reactions. Sixty-five unique MLVA types were obtained among 84 clinical non-O157 STEC strains comprised of geographically diverse sporadic and outbreak related isolates. Compared to PFGE, the developed MLVA scheme allowed similar discrimination among serogroups O26, O111, O103, and O121 but not among O145 and O45. To more fully compare the discriminatory power of this preliminary MLVA method to PFGE and to determine its epidemiological congruence, a thorough internal and external validation needs to be performed on a carefully selected large panel of strains, including multiple isolates from single outbreaks. Copyright © 2016. Published by Elsevier B.V.

Second generation subtyping: a proposed PulseNet protocol for multiple-locus variable-number tandem repeat analysis of Shiga toxin-producing Escherichia coli O157 (STEC O157).

PubMed

Hyytiä-Trees, Eija; Smole, Sandra C; Fields, Patricia A; Swaminathan, Bala; Ribot, Efrain M

2006-01-01

Most bacterial genomes contain tandem duplications of short DNA sequences, termed "variable-number tandem repeats" (VNTR). A subtyping method targeting these repeats, multiple-locus VNTR analysis (MLVA), has emerged as a powerful tool for characterization of clonal organisms such as Shiga toxin-producing Escherichia coli O157 (STEC O157). We modified and optimized a recently published MLVA scheme targeting 29 polymorphic VNTR regions of STEC O157 to render it suitable for routine use by public health laboratories that participate in PulseNet, the national and international molecular subtyping network for foodborne disease surveillance. Nine VNTR loci were included in the final protocol. They were amplified in three PCR reactions, after which the PCR products were sized using capillary electrophoresis. Two hundred geographically diverse, sporadic and outbreak- related STEC O157 isolates were characterized by MLVA and the results were compared with data obtained by pulsed-field gel electrophoresis (PFGE) using XbaI macrorestriction of genomic DNA. A total of 139 unique XbaI PFGE patterns and 162 MLVA types were identified. A subset of 100 isolates characterized by both XbaI and BlnI macrorestriction had 62 unique PFGE and MLVA types. Although the clustering of isolates by the two subtyping systems was generally in agreement, some discrepancies were observed. Importantly, MLVA was able to discriminate among some epidemiologically unrelated isolates which were indistinguishable by PFGE. However, among strains from three of the eight outbreaks included in the study, two single locus MLVA variants and one double locus variant were detected among epidemiologically implicated isolates that were indistinguishable by PFGE. Conversely, in three other outbreaks, isolates that were indistinguishable by MLVA displayed multiple PFGE types. An additional more extensive multi-laboratory validation of the MLVA protocol is in progress in order to address critical issues such as establishing epidemiologically relevant interpretation guidelines for the MLVA data.

Phenotypic and molecular characterizations of Yersinia pestis isolates from Kazakhstan and adjacent regions.

PubMed

Lowell, Jennifer L; Zhansarina, Aigul; Yockey, Brook; Meka-Mechenko, Tatyana; Stybayeva, Gulnaz; Atshabar, Bakyt; Nekrassova, Larissa; Tashmetov, Rinat; Kenghebaeva, Kuralai; Chu, May C; Kosoy, Michael; Antolin, Michael F; Gage, Kenneth L

2007-01-01

Recent interest in characterizing infectious agents associated with bioterrorism has resulted in the development of effective pathogen genotyping systems, but this information is rarely combined with phenotypic data. Yersinia pestis, the aetiological agent of plague, has been well defined genotypically on local and worldwide scales using multi-locus variable number tandem repeat analysis (MLVA), with emphasis on evolutionary patterns using old isolate collections from countries where Y. pestis has existed the longest. Worldwide MLVA studies are largely based on isolates that have been in long-term laboratory culture and storage, or on field material from parts of the world where Y. pestis has potentially circulated in nature for thousands of years. Diversity in these isolates suggests that they may no longer represent the wild-type organism phenotypically, including the possibility of altered pathogenicity. This study focused on the phenotypic and genotypic properties of 48 Y. pestis isolates collected from 10 plague foci in and bordering Kazakhstan. Phenotypic characterization was based on diagnostic tests typically performed in reference laboratories working with Y. pestis. MLVA was used to define the genotypic relationships between the central-Asian isolates and a group of North American isolates, and to examine Kazakh Y. pestis diversity according to predefined plague foci and on an intermediate geographical scale. Phenotypic properties revealed that a large portion of this collection lacks one or more plasmids necessary to complete the blocked flea/mammal transmission cycle, has lost Congo red binding capabilities (Pgm-), or both. MLVA analysis classified isolates into previously identified biovars, and in some cases groups of isolates collected within the same plague focus formed a clade. Overall, MLVA did not distinguish unique phylogeographical groups of Y. pestis isolates as defined by plague foci and indicated higher genetic diversity among older biovars.

Clostridium botulinum Group I Strain Genotyping by 15-Locus Multilocus Variable-Number Tandem-Repeat Analysis ▿ †

PubMed Central

Fillo, Silvia; Giordani, Francesco; Anniballi, Fabrizio; Gorgé, Olivier; Ramisse, Vincent; Vergnaud, Gilles; Riehm, Julia M.; Scholz, Holger C.; Splettstoesser, Wolf D.; Kieboom, Jasper; Olsen, Jaran-Strand; Fenicia, Lucia; Lista, Florigio

2011-01-01

Clostridium botulinum is a taxonomic designation that encompasses a broad variety of spore-forming, Gram-positive bacteria producing the botulinum neurotoxin (BoNT). C. botulinum is the etiologic agent of botulism, a rare but severe neuroparalytic disease. Fine-resolution genetic characterization of C. botulinum isolates of any BoNT type is relevant for both epidemiological studies and forensic microbiology. A 10-locus multiple-locus variable-number tandem-repeat analysis (MLVA) was previously applied to isolates of C. botulinum type A. The present study includes five additional loci designed to better address proteolytic B and F serotypes. We investigated 79 C. botulinum group I strains isolated from human and food samples in several European countries, including types A (28), B (36), AB (4), and F (11) strains, and 5 nontoxic Clostridium sporogenes. Additional data were deduced from in silico analysis of 10 available fully sequenced genomes. This 15-locus MLVA (MLVA-15) scheme identified 86 distinct genotypes that clustered consistently with the results of amplified fragment length polymorphism (AFLP) and MLVA genotyping in previous reports. An MLVA-7 scheme, a subset of the MLVA-15, performed on a lab-on-a-chip device using a nonfluorescent subset of primers, is also proposed as a first-line assay. The phylogenetic grouping obtained with the MLVA-7 does not differ significantly from that generated by the MLVA-15. To our knowledge, this report is the first to analyze genetic variability among all of the C. botulinum group I serotypes by MLVA. Our data provide new insights into the genetic variability of group I C. botulinum isolates worldwide and demonstrate that this group is genetically highly diverse. PMID:22012011

Clostridium botulinum group I strain genotyping by 15-locus multilocus variable-number tandem-repeat analysis.

PubMed

Fillo, Silvia; Giordani, Francesco; Anniballi, Fabrizio; Gorgé, Olivier; Ramisse, Vincent; Vergnaud, Gilles; Riehm, Julia M; Scholz, Holger C; Splettstoesser, Wolf D; Kieboom, Jasper; Olsen, Jaran-Strand; Fenicia, Lucia; Lista, Florigio

2011-12-01

Clostridium botulinum is a taxonomic designation that encompasses a broad variety of spore-forming, Gram-positive bacteria producing the botulinum neurotoxin (BoNT). C. botulinum is the etiologic agent of botulism, a rare but severe neuroparalytic disease. Fine-resolution genetic characterization of C. botulinum isolates of any BoNT type is relevant for both epidemiological studies and forensic microbiology. A 10-locus multiple-locus variable-number tandem-repeat analysis (MLVA) was previously applied to isolates of C. botulinum type A. The present study includes five additional loci designed to better address proteolytic B and F serotypes. We investigated 79 C. botulinum group I strains isolated from human and food samples in several European countries, including types A (28), B (36), AB (4), and F (11) strains, and 5 nontoxic Clostridium sporogenes. Additional data were deduced from in silico analysis of 10 available fully sequenced genomes. This 15-locus MLVA (MLVA-15) scheme identified 86 distinct genotypes that clustered consistently with the results of amplified fragment length polymorphism (AFLP) and MLVA genotyping in previous reports. An MLVA-7 scheme, a subset of the MLVA-15, performed on a lab-on-a-chip device using a nonfluorescent subset of primers, is also proposed as a first-line assay. The phylogenetic grouping obtained with the MLVA-7 does not differ significantly from that generated by the MLVA-15. To our knowledge, this report is the first to analyze genetic variability among all of the C. botulinum group I serotypes by MLVA. Our data provide new insights into the genetic variability of group I C. botulinum isolates worldwide and demonstrate that this group is genetically highly diverse.

Characterization of Escherichia coli O157:H7 in New Zealand using multiple-locus variable-number tandem-repeat analysis.

PubMed

Dyet, K H; Robertson, I; Turbitt, E; Carter, P E

2011-03-01

Recently, multiple-locus variable-number tandem-repeat analysis (MLVA) has been proposed as an alternative to pulsed-field gel electrophoresis (PFGE) for characterization of Escherichia coli O157:H7. In this study we characterized 118 E. coli O157:H7 isolates from cases of gastrointestinal disease in New Zealand using XbaI PFGE profiles and a MLVA scheme that assessed variability in eight polymorphic loci. The 118 isolates characterized included all 80 E. coli O157:H7 referred to New Zealand's Enteric Reference Laboratory in 2006 and 29 phage-type 2 isolates from 2005. When applied to these isolates the discriminatory power of PFGE and MLVA was not significantly different. However, MLVA data may be more epidemiologically relevant as isolates from family clusters of disease had identical MLVA profiles, even when the XbaI PFGE profiles differed slightly. Furthermore, most isolates with indistinguishable XbaI PFGE profiles that did not appear to be epidemiologically related had distinct MLVA profiles.

A multiple-locus variable-number tandem repeat analysis (MLVA) of Listeria monocytogenes isolated from Norwegian salmon-processing factories and from listeriosis patients.

PubMed

Lunestad, B T; Truong, T T T; Lindstedt, B-A

2013-10-01

The objective of this study was to characterize Listeria monocytogenes isolated from farmed Atlantic salmon (Salmo salar) and the processing environment in three different Norwegian factories, and compare these to clinical isolates by multiple-locus variable-number tandem repeat analysis (MLVA). The 65 L. monocytogenes isolates obtained gave 15 distinct MLVA profiles. There was great heterogeneity in the distribution of MLVA profiles in factories and within each factory. Nine of the 15 MLVA profiles found in the fish-associated isolates were found to match human profiles. The MLVA profile 07-07-09-10-06 was the most common strain in Norwegian listeriosis patients. L. monocytogenes with this profile has previously been associated with at least two known listeriosis outbreaks in Norway, neither determined to be due to fish consumption. However, since this profile was also found in fish and in the processing environment, fish should be considered as a possible food vehicle during sporadic cases and outbreaks of listeriosis.

Multilocus variable-number tandem repeat analysis distinguishes outbreak and sporadic Escherichia coli O157:H7 isolates.

PubMed

Noller, Anna C; McEllistrem, M Catherine; Pacheco, Antonio G F; Boxrud, David J; Harrison, Lee H

2003-12-01

Escherichia coli O157:H7 is a major cause of food-borne illness in the United States. Outbreak detection involves traditional epidemiological methods and routine molecular subtyping by pulsed-field gel electrophoresis (PFGE). PFGE is labor-intensive, and the results are difficult to analyze and not easily transferable between laboratories. Multilocus variable-number tandem repeat (VNTR) analysis (MLVA) is a fast, portable method that analyzes multiple VNTR loci, which are areas of the bacterial genome that evolve quickly. Eighty isolates, including 21 isolates from five epidemiologically well-characterized outbreaks from Pennsylvania and Minnesota, were analyzed by PFGE and MLVA. Strains in PFGE clusters were defined as strains that differed by less than or equal to one band by using XbaI and the confirmatory enzyme SpeI. MLVA was performed by comparing the number of tandem repeats at seven loci. From 6 to 30 alleles were found at the seven loci, resulting in 64 MLVA types among the 80 isolates. MLVA correctly identified the isolates from all five outbreaks if only a single-locus variant was allowed. MLVA differentiated strains with unique PFGE types. Additionally, MLVA discriminated strains within PFGE-defined clusters that were not known to be part of an outbreak. In addition to being a simple and validated method for E. coli O157:H7 outbreak detection, MLVA appears to have a sensitivity equal to that of PFGE and a specificity superior to that of PFGE.

Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark.

PubMed

de Knegt, Leonardo V; Pires, Sara M; Löfström, Charlotta; Sørensen, Gitte; Pedersen, Karl; Torpdahl, Mia; Nielsen, Eva M; Hald, Tine

2016-03-01

Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal-food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping-based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping-based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi-locus sequence typing or next-generation sequencing techniques. © 2015 Society for Risk Analysis.

Multi-locus variable-number tandem repeat analysis for outbreak studies of Salmonella enterica serotype Enteritidis

PubMed Central

Malorny, Burkhard; Junker, Ernst; Helmuth, Reiner

2008-01-01

Background Salmonella enterica subsp. enterica serotype Enteritidis is known as an important and pathogenic clonal group which continues to cause worldwide sporadic cases and outbreaks in humans. Here a new multiple-locus variable-number tandem repeat analysis (MLVA) method is reported for highly-discriminative subtyping of Salmonella Enteritidis. Emphasis was given on the most predominant phage types PT4 and PT8. The method comprises multiplex PCR specifically amplifying repeated sequences from nine different loci followed by an automatic fragment size analysis using a multicolor capillary electrophoresis instrument. A total of 240 human, animal, food and environmental isolates of S. Enteritidis including 23 definite phage types were used for development and validation. Furthermore, the MLVA types were compared to the phage types of several isolates from two recent outbreaks to determine the concordance between both methods and to estimate their in vivo stability. The in vitro stability of the two MLVA types specifically for PT4 and PT8 strains were determined by multiple freeze-thaw cycles. Results Seventy-nine different MLVA types were identified in 240 S. Enteritidis strains. The Simpson's diversity index for the MLVA method was 0.919 and Nei diversity values for the nine VNTR loci ranged from 0.07 to 0.65. Twenty-four MLVA types could be assigned to 62 PT4 strains and 21 types to 81 PT8 strains. All outbreak isolates had an indistinguishable outbreak specific MLVA type. The in vitro stability experiments showed no changes of the MLVA type compared to the original isolate. Conclusion This MLVA method is useful to discriminate S. Enteritidis strains even within a single phage type. It is easy in use, fast, and cheap compared to other high-resolution molecular methods and therefore an important tool for surveillance and outbreak studies for S. Enteritidis. PMID:18513386

Multiple-locus variable-number tandem-repeat analysis of the swine dysentery pathogen, Brachyspira hyodysenteriae.

PubMed

Hidalgo, Alvaro; Carvajal, Ana; La, Tom; Naharro, Germán; Rubio, Pedro; Phillips, Nyree D; Hampson, David J

2010-08-01

The spirochete Brachyspira hyodysenteriae is the causative agent of swine dysentery, a severe colonic infection of pigs that has a considerable economic impact in many swine-producing countries. In spite of its importance, knowledge about the global epidemiology and population structure of B. hyodysenteriae is limited. Progress in this area has been hampered by the lack of a low-cost, portable, and discriminatory method for strain typing. The aim of the current study was to develop and test a multiple-locus variable-number tandem-repeat analysis (MLVA) method that could be used in basic veterinary diagnostic microbiology laboratories equipped with PCR technology or in more advanced laboratories with access to capillary electrophoresis. Based on eight loci, and when performed on isolates from different farms in different countries, as well as type and reference strains, the MLVA technique developed was highly discriminatory (Hunter and Gaston discriminatory index, 0.938 [95% confidence interval, 0.9175 to 0.9584]) while retaining a high phylogenetic value. Using the technique, the species was shown to be diverse (44 MLVA types from 172 isolates and strains), although isolates were stable in herds over time. The population structure appeared to be clonal. The finding of B. hyodysenteriae MLVA type 3 in piggeries in three European countries, as well as other, related, strains in different countries, suggests that spreading of the pathogen via carrier pigs is likely. MLVA overcame drawbacks associated with previous typing techniques for B. hyodysenteriae and was a powerful method for epidemiologic and population structure studies on this important pathogenic spirochete.

Genetic Diversity among Bacillus anthracis Soil Isolates at Fine Geographic Scales

PubMed Central

Bader, Douglas E.

2012-01-01

Environmental samples were collected from carcass sites during and after anthrax outbreaks in 2000 and 2001 in the bison (Bison bison) population within Wood Buffalo National Park and the Hook Lake Region north of Wood Buffalo National Park. Bacillus anthracis spores were isolated from these samples and confirmed using phenotypic characterization and real-time PCR. Confirmed B. anthracis isolates were typed using multiple-locus variable-number tandem repeat analysis (MLVA15) and single-nucleotide-repeat analysis (SNRA). B. anthracis isolates split into two clades based on MLVA15, while SNRA allowed some isolates between carcass sites to be distinguished from each other. SNRA polymorphisms were also present within a single carcass site. Some isolates from different carcass sites having the same SNRA type had divergent MLVA types; this finding leads to questions about hierarchical typing methods and the robustness of the fine-scale typing of Bacillus anthracis. PMID:22773624

Molecular characterization of Verocytotoxigenic Escherichia coli O157:H7 isolates from Argentina by Multiple-Loci VNTR Analysis (MLVA).

PubMed

Bustamante, Ana V; Lucchesi, Paula M A; Parma, Alberto E

2009-10-01

The aim of this work was to adapt described MLVA protocols to the molecular typing and characterization of VTEC O157:H7 isolates from Argentina. Nine VNTR loci were amplified by PCR showing diversity values from 0.49 to 0.73. Nine MLVA profiles were observed and the cluster analysis indicated both unrelated and closely related VTEC O157:H7 strains. In spite of the limited number of isolates studied, the panel of VNTR used made it possible to perform a first approach of the high genetic diversity of native strains of O157:H7 by MLVA.

Multiple-locus variable-number tandem-repeats analysis of Listeria monocytogenes using multicolour capillary electrophoresis and comparison with pulsed-field gel electrophoresis typing.

PubMed

Lindstedt, Bjørn-Arne; Tham, Wilhelm; Danielsson-Tham, Marie-Louise; Vardund, Traute; Helmersson, Seved; Kapperud, Georg

2008-02-01

The multiple-locus variable-number tandem-repeats analysis (MLVA) method for genotyping has proven to be a fast and reliable typing tool in several bacterial species. MLVA is in our laboratory the routine typing method for Salmonella enterica subsp. enterica serovar Typhimurium and Escherichia coli O157. The gram-positive bacteria Listeria monocytogenes, while not isolated as frequent as S. Typhimurium and E. coli, causes severe illness with an overall mortality rate of 30%. Thus, it is important that any outbreak of this pathogen is detected early and a fast trace to the source can be performed. In view of this, we have used the information provided by two fully sequenced L. monocytogenes strains to develop a MLVA assay coupled with high-resolution capillary electrophoresis and compared it to pulsed-field gel electrophoresis (PFGE) in two sets of isolates, one Norwegian (79 isolates) and one Swedish (61 isolates) set. The MLVA assay could resolve all of the L. monocytogenes serotypes tested, and was slightly more discriminatory than PFGE for the Norwegian isolates (28 MLVA profiles and 24 PFGE profiles) and opposite for the Swedish isolates (42 MLVA profiles and 43 PFGE profiles).

Subtyping of STEC by MLVA in Argentina.

PubMed

Bustamante, Ana V; Sanso, Andrea M; Parma, Alberto E; Lucchesi, Paula M A

2012-01-01

Shiga toxin-producing Escherichia coli (STEC) causes serious human illness such as hemolytic uremic syndrome (HUS). Argentina has the world's highest rate of this syndrome, which is the leading cause of acute renal failure among children. E. coli O157:H7 is the most common cause of HUS, but a substantial and growing proportion of this illness is caused by infection due to non-O157 strains. Multiple-locus variable-number tandem repeat analysis (MLVA) has become an established technique to subtype STEC. This review will address the use of routine STEC subtyping by MLVA in order to type this group of isolates and to get insight into the genetic diversity of native STEC. With regard to these objectives we modified and adapted two MLVA protocols, one exclusive for O157 and the other, a generic E. coli assay. A total of 202 STEC isolates, from different sources and corresponding to 20 serotypes, have been MLVA genotyped in our laboratory. In our experience, MLVA constitutes a very sensitive tool and enables us to perform an efficient STEC subtyping. The diversity found in many serotypes may be useful for future epidemiological studies of STEC clonality, applied to O157 as well as to non-O157 isolates.

Genetic relatedness of Brucella suis biovar 2 isolates from hares, wild boars and domestic pigs.

PubMed

Kreizinger, Zsuzsa; Foster, Jeffrey T; Rónai, Zsuzsanna; Sulyok, Kinga M; Wehmann, Enikő; Jánosi, Szilárd; Gyuranecz, Miklós

2014-08-27

Porcine brucellosis generally manifests as disorders in reproductive organs potentially leading to serious losses in the swine industry. Brucella suis biovar 2 is endemic in European wild boar (Sus scrofa) and hare (Lepus europeus, Lepus capensis) populations, thus these species may play a significant role in disease spread and serve as potential sources of infection for domestic pigs. The aim of this study was an epidemiologic analysis of porcine brucellosis in Hungary and a comparative analysis of B. suis bv. 2 strains from Europe using multiple-locus variable-number tandem repeat analysis (MLVA). MLVA-16 and its MLVA-11 subset were used to determine the genotypes of 68 B. suis bv. 2 isolates from Hungary and results were then compared to European MLVA genotypes. The analyses indicated relatively high genetic diversity of B. suis bv. 2 in Hungary. Strains isolated from hares and wild boars from Hungary showed substantial genetic divergence, suggesting separate lineages in each host and no instances of cross species infections. The closest relatives of strains from Hungarian wild boars and domestic pigs were mainly in the isolates from German and Croatian boars and pigs. The assessment of the European MLVA genotypes of wild boar isolates generally showed clustering based on geographic origin. The hare strains were relatively closely related to one another and did not cluster based on geographic origin. The limited relationships between geographic origin and genotype in isolates from hares might be the result of cross-border live animal translocation. The results could also suggest that certain B. suis strains are more adapted to hares. Across Europe, isolates from domestic pigs were closely related to isolates originating from both hares and wild boars, supporting the idea that wild animals are a source of brucellosis in domestic pigs. Copyright © 2014 Elsevier B.V. All rights reserved.

Molecular characterization of Verocytotoxigenic Escherichia coli O157:H7 isolates from Argentina by Multiple-Loci VNTR Analysis (MLVA)

PubMed Central

Bustamante, Ana V.; Lucchesi, Paula M.A.; Parma, Alberto E.

2009-01-01

The aim of this work was to adapt described MLVA protocols to the molecular typing and characterization of VTEC O157:H7 isolates from Argentina. Nine VNTR loci were amplified by PCR showing diversity values from 0.49 to 0.73. Nine MLVA profiles were observed and the cluster analysis indicated both unrelated and closely related VTEC O157:H7 strains. In spite of the limited number of isolates studied, the panel of VNTR used made it possible to perform a first approach of the high genetic diversity of native strains of O157:H7 by MLVA. PMID:24031443

Multi-laboratory validation study of multilocus variable-number tandem repeat analysis (MLVA) for Salmonella enterica serovar Enteritidis, 2015

PubMed Central

Peters, Tansy; Bertrand, Sophie; Björkman, Jonas T; Brandal, Lin T; Brown, Derek J; Erdõsi, Tímea; Heck, Max; Ibrahem, Salha; Johansson, Karin; Kornschober, Christian; Kotila, Saara M; Le Hello, Simon; Lienemann, Taru; Mattheus, Wesley; Nielsen, Eva Møller; Ragimbeau, Catherine; Rumore, Jillian; Sabol, Ashley; Torpdahl, Mia; Trees, Eija; Tuohy, Alma; de Pinna, Elizabeth

2017-01-01

Multilocus variable-number tandem repeat analysis (MLVA) is a rapid and reproducible typing method that is an important tool for investigation, as well as detection, of national and multinational outbreaks of a range of food-borne pathogens. Salmonella enterica serovar Enteritidis is the most common Salmonella serovar associated with human salmonellosis in the European Union/European Economic Area and North America. Fourteen laboratories from 13 countries in Europe and North America participated in a validation study for MLVA of S. Enteritidis targeting five loci. Following normalisation of fragment sizes using a set of reference strains, a blinded set of 24 strains with known allele sizes was analysed by each participant. The S. Enteritidis 5-loci MLVA protocol was shown to produce internationally comparable results as more than 90% of the participants reported less than 5% discrepant MLVA profiles. All 14 participating laboratories performed well, even those where experience with this typing method was limited. The raw fragment length data were consistent throughout, and the inter-laboratory validation helped to standardise the conversion of raw data to repeat numbers with at least two countries updating their internal procedures. However, differences in assigned MLVA profiles remain between well-established protocols and should be taken into account when exchanging data. PMID:28277220

Subtyping of STEC by MLVA in Argentina

PubMed Central

Bustamante, Ana V.; Sanso, Andrea M.; Parma, Alberto E.; Lucchesi, Paula M. A.

2012-01-01

Shiga toxin-producing Escherichia coli (STEC) causes serious human illness such as hemolytic uremic syndrome (HUS). Argentina has the world’s highest rate of this syndrome, which is the leading cause of acute renal failure among children. E. coli O157:H7 is the most common cause of HUS, but a substantial and growing proportion of this illness is caused by infection due to non-O157 strains. Multiple-locus variable-number tandem repeat analysis (MLVA) has become an established technique to subtype STEC. This review will address the use of routine STEC subtyping by MLVA in order to type this group of isolates and to get insight into the genetic diversity of native STEC. With regard to these objectives we modified and adapted two MLVA protocols, one exclusive for O157 and the other, a generic E. coli assay. A total of 202 STEC isolates, from different sources and corresponding to 20 serotypes, have been MLVA genotyped in our laboratory. In our experience, MLVA constitutes a very sensitive tool and enables us to perform an efficient STEC subtyping. The diversity found in many serotypes may be useful for future epidemiological studies of STEC clonality, applied to O157 as well as to non-O157 isolates. PMID:22919698

A novel typing method for Listeria monocytogenes using high-resolution melting analysis (HRMA) of tandem repeat regions.

PubMed

Ohshima, Chihiro; Takahashi, Hajime; Iwakawa, Ai; Kuda, Takashi; Kimura, Bon

2017-07-17

Listeria monocytogenes, which is responsible for causing food poisoning known as listeriosis, infects humans and animals. Widely distributed in the environment, this bacterium is known to contaminate food products after being transmitted to factories via raw materials. To minimize the contamination of products by food pathogens, it is critical to identify and eliminate factory entry routes and pathways for the causative bacteria. High resolution melting analysis (HRMA) is a method that takes advantage of differences in DNA sequences and PCR product lengths that are reflected by the disassociation temperature. Through our research, we have developed a multiple locus variable-number tandem repeat analysis (MLVA) using HRMA as a simple and rapid method to differentiate L. monocytogenes isolates. While evaluating our developed method, the ability of MLVA-HRMA, MLVA using capillary electrophoresis, and multilocus sequence typing (MLST) was compared for their ability to discriminate between strains. The MLVA-HRMA method displayed greater discriminatory ability than MLST and MLVA using capillary electrophoresis, suggesting that the variation in the number of repeat units, along with mutations within the DNA sequence, was accurately reflected by the melting curve of HRMA. Rather than relying on DNA sequence analysis or high-resolution electrophoresis, the MLVA-HRMA method employs the same process as PCR until the analysis step, suggesting a combination of speed and simplicity. The result of MLVA-HRMA method is able to be shared between different laboratories. There are high expectations that this method will be adopted for regular inspections at food processing facilities in the near future. Copyright © 2017. Published by Elsevier B.V.

Staphylococcus aureus from 152 cases of bovine, ovine and caprine mastitis investigated by Multiple-locus variable number of tandem repeat analysis (MLVA).

PubMed

Bergonier, Dominique; Sobral, Daniel; Feßler, Andrea T; Jacquet, Eric; Gilbert, Florence B; Schwarz, Stefan; Treilles, Michaël; Bouloc, Philippe; Pourcel, Christine; Vergnaud, Gilles

2014-10-02

Staphylococcus aureus is one of the main etiological agents of mastitis in ruminants. In the present retrospective study, we evaluated the potential interest of a previously described automated multiple loci Variable Number of Tandem Repeats (VNTR) Assay (MLVA) comprising 16 loci as a first line tool to investigate the population structure of S. aureus from mastitis. We determined the genetic diversity of S. aureus strains from cases of clinical and subclinical mastitis in dairy cattle (n = 118, of which 16 were methicillin-resistant), sheep (n = 18) and goats (n = 16). The 152 strains could be subdivided into 115 MLVA genotypes (including 14 genotypes for the ovine strains and 15 genotypes for the caprine strains). This corresponds to a discriminatory index (D) value of 0.9936. Comparison with published MLVA data obtained using the same protocol applied to strains from diverse human and animal origins revealed a low number (8.5%) of human-related MLVA genotypes among the present collection. Eighteen percent of the S. aureus mastitis collection belonged to clonal complexes apparently not associated with other pathological conditions. Some of them displayed a relatively low level of diversity in agreement with a restricted ecological niche. These findings provide arguments suggesting that specific S. aureus lineages particularly adapted to ruminant mammary glands have emerged and that MLVA is a convenient tool to provide a broad overview of the population, owing to the availability via internet of databases compiling published MLVA genotypes.

Preliminary Investigation on Multiple-Locus Variable Number Tandem Repeat Analysis Profiles of Listeria Monocytogenes Isolates from Pork Meat Tested from Packaging to Fork

PubMed Central

Parisi, Antonio; Caruso, Marta; Pasquali, Frédérique; Manfreda, Gerardo

2014-01-01

Listeria monocytogenes is recognised as a public health issue and a serious challenge for the food industry. L. monocytogenes strain characterisation on the basis of serotyping and molecular typing methods is used for surveillance, epidemiological tracking and outbreak investigation purposes. Genetic variants of L. monocytogenes have diversified into four major phylogenetic lineages, with lineages 1 and 2 each containing multiple clonal groups of public health importance. Standardised tools for easy identification of clonal groups are needed to trace such groups and determine their presence in a large variety of sources. Given the current limitations of available methods for L. monocytogenes strain typing, a potentially useful approach is multiple locus variable number of tandem repeats (VNTR) analysis (MLVA). In this study, MLVA has been applied to a random group of 82 L. monocytogenes strains isolated from 8 different batches of loin chops obtained from the same facility and tested between packaging and consumption time. The strains typed were classified into 10 MLVA profiles containing a number of isolates ranging between 1 to 20. According to the identified MLVA profiles, 75.6% of the pork isolates belonged to the phylogenetic lineage 2 and serotype 1/2c, frequently associated to food isolates. However, 3 pork strains belonged to the phylogenetic lineage 1 and serotype 4b. Moreover, 17 isolates were classified in the phylogenetic lineages 2 and serotype 1/2a. Both serotypes 4b and 1/2a are frequently associated to human isolates of L. monocytogenes. These preliminary results show how the MLVA profiles can support the assessment of the risk profile of food products based on the contaminating L. monocytogenes strain types. PMID:27800312

Epidemiology of Brucellosis and Genetic Diversity of Brucella abortus in Kazakhstan

PubMed Central

Shevtsova, Elena; Shevtsov, Alexandr; Mukanov, Kasim; Filipenko, Maxim; Kamalova, Dinara; Sytnik, Igor; Syzdykov, Marat; Kuznetsov, Andrey; Akhmetova, Assel; Zharova, Mira; Karibaev, Talgat; Tarlykov, Pavel; Ramanculov, Erlan

2016-01-01

Brucellosis is a major zoonotic infection in Kazakhstan. However, there is limited data on its incidence in humans and animals, and the genetic diversity of prevalent strains is virtually unstudied. Additionally, there is no detailed overview of Kazakhstan brucellosis control and eradication programs. Here, we analyzed brucellosis epidemiological data, and assessed the effectiveness of eradication strategies employed over the past 70 years to counteract this infection. We also conducted multiple loci variable-number tandem repeat analysis (MLVA) of Brucella abortus strains found in Kazakhstan. We analyzed official data on the incidence of animal brucellosis in Kazakhstan. The records span more than 70 years of anti-brucellosis campaigns, and contain a brief description of the applied control strategies, their effectiveness, and their impact on the incidence in humans. The MLVA-16 method was used to type 94 strains of B. abortus and serial passages of B. abortus 82, a strain used in vaccines. MLVA-8 and MLVA-11 analyses clustered strains into a total of four and seven genotypes, respectively; it is the first time that four of these genotypes have been described. MLVA-16 analysis divided strains into 28 distinct genotypes having genetic similarity coefficient that varies from 60 to100% and a Hunter & Gaston diversity index of 0.871. MST analysis reconstruction revealed clustering into "Kazakhstani-Chinese (Central Asian)", "European" and "American" lines. Detection of multiple genotypes in a single outbreak confirms that poorly controlled trade of livestock plays a crucial role in the spread of infection. Notably, the MLVA-16 profile of the B. abortus 82 strain was unique and did not change during 33 serial passages. MLVA genotyping may thus be useful for epidemiological monitoring of brucellosis, and for tracking the source(s) of infection. We suggest that countrywide application of MLVA genotyping would improve the control of brucellosis in Kazakhstan. PMID:27907105

Epidemiology of Brucellosis and Genetic Diversity of Brucella abortus in Kazakhstan.

PubMed

Shevtsova, Elena; Shevtsov, Alexandr; Mukanov, Kasim; Filipenko, Maxim; Kamalova, Dinara; Sytnik, Igor; Syzdykov, Marat; Kuznetsov, Andrey; Akhmetova, Assel; Zharova, Mira; Karibaev, Talgat; Tarlykov, Pavel; Ramanculov, Erlan

2016-01-01

Brucellosis is a major zoonotic infection in Kazakhstan. However, there is limited data on its incidence in humans and animals, and the genetic diversity of prevalent strains is virtually unstudied. Additionally, there is no detailed overview of Kazakhstan brucellosis control and eradication programs. Here, we analyzed brucellosis epidemiological data, and assessed the effectiveness of eradication strategies employed over the past 70 years to counteract this infection. We also conducted multiple loci variable-number tandem repeat analysis (MLVA) of Brucella abortus strains found in Kazakhstan. We analyzed official data on the incidence of animal brucellosis in Kazakhstan. The records span more than 70 years of anti-brucellosis campaigns, and contain a brief description of the applied control strategies, their effectiveness, and their impact on the incidence in humans. The MLVA-16 method was used to type 94 strains of B. abortus and serial passages of B. abortus 82, a strain used in vaccines. MLVA-8 and MLVA-11 analyses clustered strains into a total of four and seven genotypes, respectively; it is the first time that four of these genotypes have been described. MLVA-16 analysis divided strains into 28 distinct genotypes having genetic similarity coefficient that varies from 60 to100% and a Hunter & Gaston diversity index of 0.871. MST analysis reconstruction revealed clustering into "Kazakhstani-Chinese (Central Asian)", "European" and "American" lines. Detection of multiple genotypes in a single outbreak confirms that poorly controlled trade of livestock plays a crucial role in the spread of infection. Notably, the MLVA-16 profile of the B. abortus 82 strain was unique and did not change during 33 serial passages. MLVA genotyping may thus be useful for epidemiological monitoring of brucellosis, and for tracking the source(s) of infection. We suggest that countrywide application of MLVA genotyping would improve the control of brucellosis in Kazakhstan.

Multi-laboratory validation study of multilocus variable-number tandem repeat analysis (MLVA) for Salmonella enterica serovar Enteritidis, 2015.

PubMed

Peters, Tansy; Bertrand, Sophie; Björkman, Jonas T; Brandal, Lin T; Brown, Derek J; Erdõsi, Tímea; Heck, Max; Ibrahem, Salha; Johansson, Karin; Kornschober, Christian; Kotila, Saara M; Le Hello, Simon; Lienemann, Taru; Mattheus, Wesley; Nielsen, Eva Møller; Ragimbeau, Catherine; Rumore, Jillian; Sabol, Ashley; Torpdahl, Mia; Trees, Eija; Tuohy, Alma; de Pinna, Elizabeth

2017-03-02

Multilocus variable-number tandem repeat analysis (MLVA) is a rapid and reproducible typing method that is an important tool for investigation, as well as detection, of national and multinational outbreaks of a range of food-borne pathogens. Salmonella enterica serovar Enteritidis is the most common Salmonella serovar associated with human salmonellosis in the European Union/European Economic Area and North America. Fourteen laboratories from 13 countries in Europe and North America participated in a validation study for MLVA of S. Enteritidis targeting five loci. Following normalisation of fragment sizes using a set of reference strains, a blinded set of 24 strains with known allele sizes was analysed by each participant. The S. Enteritidis 5-loci MLVA protocol was shown to produce internationally comparable results as more than 90% of the participants reported less than 5% discrepant MLVA profiles. All 14 participating laboratories performed well, even those where experience with this typing method was limited. The raw fragment length data were consistent throughout, and the inter-laboratory validation helped to standardise the conversion of raw data to repeat numbers with at least two countries updating their internal procedures. However, differences in assigned MLVA profiles remain between well-established protocols and should be taken into account when exchanging data. This article is copyright of The Authors, 2017.

Spatial epidemiology of Escherichia coli O157:H7 in dairy cattle in relation to night roosts Of Sturnus vulgaris (European Starling) in Ohio, USA (2007-2009).

PubMed

Swirski, A L; Pearl, D L; Williams, M L; Homan, H J; Linz, G M; Cernicchiaro, N; LeJeune, J T

2014-09-01

The goal of our study was to use spatial scan statics to determine whether the night roosts of European starlings (Sturnus vulgaris) act as point sources for the dissemination of Escherichia coli O157:H7 among dairy farms. From 2007 to 2009, we collected bovine faecal samples (n = 9000) and starling gastrointestinal contents (n = 430) from 150 dairy farms in northeastern Ohio, USA. Isolates of E. coli O157:H7 recovered from these samples were subtyped using multilocus variable-number tandem repeat analysis (MLVA). Generated MLVA types were used to construct a dendrogram based on a categorical multistate coefficient and unweighted pair-group method with arithmetic mean (UPGMA). Using a focused spatial scan statistic, we identified statistically significant spatial clusters among dairy farms surrounding starling night roosts, with an increased prevalence of E. coli O157:H7-positive bovine faecal pats, increased diversity of distinguishable MLVA types and a greater number of isolates with MLVA types from bovine-starling clades versus bovine-only clades. Thus, our findings are compatible with the hypothesis that starlings have a role in the dissemination of E. coli O157:H7 among dairy farms, and further research into starling management is warranted. © 2013 Blackwell Verlag GmbH.

Multiple-Locus Variable-Number Tandem-Repeats Analysis of Escherichia coli O157 using PCR multiplexing and multi-colored capillary electrophoresis.

PubMed

Lindstedt, Bjørn-Arne; Vardund, Traute; Kapperud, Georg

2004-08-01

The Multiple-Locus Variable-Number Tandem-Repeats Analysis (MLVA) method is currently being used as the primary typing tool for Shiga-toxin-producing Escherichia coli (STEC) O157 isolates in our laboratory. The initial assay was performed using a single fluorescent dye and the different patterns were assigned using a gel image. Here, we present a significantly improved assay using multiple dye colors and enhanced PCR multiplexing to increase speed, and ease the interpretation of the results. The different MLVA patterns are now based on allele sizes entered as character values, thus removing the uncertainties introduced when analyzing band patterns from the gel image. We additionally propose an easy numbering scheme for the identification of separate isolates that will facilitate exchange of typing data. Seventy-two human and animal strains of Shiga-toxin-producing E. coli O157 were used for the development of the improved MLVA assay. The method is based on capillary separation of multiplexed PCR products of VNTR loci in the E. coli O157 genome labeled with multiple fluorescent dyes. The different alleles at each locus were then assigned to allele numbers, which were used for strain comparison.

Rapid and high resolution genotyping of all Escherichia coli serotypes using 10 genomic repeat-containing loci.

PubMed

Løbersli, Inger; Haugum, Kjersti; Lindstedt, Bjørn-Arne

2012-01-01

Our laboratory has previously published two multiple-locus variable-number tandem-repeats analysis (MLVA) methods for rapid genotyping of Escherichia coli (E. coli), which are now in routine use for surveillance and outbreak detection. The first assay developed was specific for E. coli O157:H7; however this assay was not suitable for genotyping other E. coli serotypes. A new generic MLVA-assay was then developed with the capability of genotyping all E. coli serotypes. This generic E. coli MLVA (GECM7) was based on polymorphism in seven variable number of tandem repeats (VNTR) loci. GECM7 worked well with the majority of E. coli serotypes; however we wanted to increase the resolution for this method based in part of comparison with PFGE typing of E. coli O26:H11, where PFGE appeared to display higher resolution. The GECM7 method was improved by adding three new repeat-loci to a total of ten (GECM10), and a considerable increase in resolution was observed (from 296 to 507 genotypes on the same set of strains). Copyright © 2011 Elsevier B.V. All rights reserved.

Genotyping of Coxiella burnetii from domestic ruminants in northern Spain.

PubMed

Astobiza, Ianire; Tilburg, Jeroen J H C; Piñero, Alvaro; Hurtado, Ana; García-Pérez, Ana L; Nabuurs-Franssen, Marrigje H; Klaassen, Corné H W

2012-12-10

Information on the genotypic diversity of Coxiella burnetii isolates from infected domestic ruminants in Spain is limited. The aim of this study was to identify the C. burnetii genotypes infecting livestock in Northern Spain and compare them to other European genotypes. A commercial real-time PCR targeting the IS1111a insertion element was used to detect the presence of C. burnetii DNA in domestic ruminants from Spain. Genotypes were determined by a 6-loci Multiple Locus Variable number tandem repeat analysis (MLVA) panel and Multispacer Sequence Typing (MST). A total of 45 samples from 4 goat herds (placentas, N = 4), 12 dairy cattle herds (vaginal mucus, individual milk, bulk tank milk, aerosols, N = 20) and 5 sheep flocks (placenta, vaginal swabs, faeces, air samples, dust, N = 21) were included in the study. Samples from goats and sheep were obtained from herds which had suffered abortions suspected to be caused by C. burnetii, whereas cattle samples were obtained from animals with reproductive problems compatible with C. burnetii infection, or consisted of bulk tank milk (BTM) samples from a Q fever surveillance programme. C. burnetii genotypes identified in ruminants from Spain were compared to those detected in other countries. Three MLVA genotypes were found in 4 goat farms, 7 MLVA genotypes were identified in 12 cattle herds and 4 MLVA genotypes were identified in 5 sheep flocks. Clustering of the MLVA genotypes using the minimum spanning tree method showed a high degree of genetic similarity between most MLVA genotypes. Overall 11 different MLVA genotypes were obtained corresponding to 4 different MST genotypes: MST genotype 13, identified in goat, sheep and cattle from Spain; MST genotype 18, only identified in goats; and, MST genotypes 8 and 20, identified in small ruminants and cattle, respectively. All these genotypes had been previously identified in animal and human clinical samples from several European countries, but some of the MLVA genotypes are described here for the first time. Genotyping revealed a substantial genetic diversity among domestic ruminants from Northern Spain.

Genetic source tracking of an anthrax outbreak in Shaanxi province, China.

PubMed

Liu, Dong-Li; Wei, Jian-Chun; Chen, Qiu-Lan; Guo, Xue-Jun; Zhang, En-Min; He, Li; Liang, Xu-Dong; Ma, Guo-Zhu; Zhou, Ti-Cao; Yin, Wen-Wu; Liu, Wei; Liu, Kai; Shi, Yi; Ji, Jian-Jun; Zhang, Hui-Juan; Ma, Lin; Zhang, Fa-Xin; Zhang, Zhi-Kai; Zhou, Hang; Yu, Hong-Jie; Kan, Biao; Xu, Jian-Guo; Liu, Feng; Li, Wei

2017-01-17

Anthrax is an acute zoonotic infectious disease caused by the bacterium known as Bacillus anthracis. From 26 July to 8 August 2015, an outbreak with 20 suspected cutaneous anthrax cases was reported in Ganquan County, Shaanxi province in China. The genetic source tracking analysis of the anthrax outbreak was performed by molecular epidemiological methods in this study. Three molecular typing methods, namely canonical single nucleotide polymorphisms (canSNP), multiple-locus variable-number tandem repeat analysis (MLVA), and single nucleotide repeat (SNR) analysis, were used to investigate the possible source of transmission and identify the genetic relationship among the strains isolated from human cases and diseased animals during the outbreak. Five strains isolated from diseased mules were clustered together with patients' isolates using canSNP typing and MLVA. The causative B. anthracis lineages in this outbreak belonged to the A.Br.001/002 canSNP subgroup and the MLVA15-31 genotype (the 31 genotype in MLVA15 scheme). Because nine isolates from another four provinces in China were clustered together with outbreak-related strains by the canSNP (A.Br.001/002 subgroup) and MLVA15 method (MLVA15-31 genotype), still another SNR analysis (CL10, CL12, CL33, and CL35) was used to source track the outbreak, and the results suggesting that these patients in the anthrax outbreak were probably infected by the same pathogen clone. It was deduced that the anthrax outbreak occurred in Shaanxi province, China in 2015 was a local occurrence.

Molecular epidemiology of Bordetella pertussis in Greece, 2010-2015.

PubMed

Petridou, Evangelia; Jensen, Christel Barker; Arvanitidis, Athanasios; Giannaki-Psinaki, Maria; Michos, Athanasios; Krogfelt, Karen Angeliki; Petersen, Randi Føns

2018-03-01

To determine the predominant strains of Bordetella pertussis in Greece during 2010-2015. Infants and children (n=1150) (15 days to 14 years) of Greek, Roma and immigrant origin with different vaccination statuses were hospitalized in Athens, Greece with suspected pertussis infection. IS481/IS1001 real-time PCR confirmed Bordetella spp./B. pertussis infection in 300 samples. A subset of samples (n=153) were analysed by multi-locus variable number tandem repeat analysis (MLVA) and (n=25) by sequence-based typing of the toxin promotor region (ptxP) on DNA extracted from clinical specimens.Results/Key findings. A complete MLVA profile was determined in 66 out of 153 samples; the B. pertussis MLVA type 27 (n=55) was the dominant genotype and all tested samples (n=25) expressed the ptxP3 genotype. The vaccine coverage in the Greek population was 90 %; however, the study population expressed complete coverage in 2 out of 264 infants (0-11 months) and in 20 out of 36 children (1-14 years). Roma and immigrant minorities represent 7 % of the Greek population, but make up 50 % of the study population, indicating a low vaccine coverage among these groups. The B. pertussis MT27 and ptxP3 genotype is dominant in Greek, Roma and immigrant infants and children hospitalized in Greece. Thus, the predominant MLVA genotype in Greece is similar to other countries using acellular vaccines.

Molecular epidemiology of Bordetella pertussis in Greece, 2010–2015

PubMed Central

Arvanitidis, Athanasios; Giannaki-Psinaki, Maria; Michos, Athanasios; Krogfelt, Karen Angeliki; Petersen, Randi Føns

2018-01-01

Purpose To determine the predominant strains of Bordetella pertussis in Greece during 2010–2015. Methodology Infants and children (n=1150) (15 days to 14 years) of Greek, Roma and immigrant origin with different vaccination statuses were hospitalized in Athens, Greece with suspected pertussis infection. IS481/IS1001 real-time PCR confirmed Bordetella spp./B. pertussis infection in 300 samples. A subset of samples (n=153) were analysed by multi-locus variable number tandem repeat analysis (MLVA) and (n=25) by sequence-based typing of the toxin promotor region (ptxP) on DNA extracted from clinical specimens. Results/Key findings A complete MLVA profile was determined in 66 out of 153 samples; the B. pertussis MLVA type 27 (n=55) was the dominant genotype and all tested samples (n=25) expressed the ptxP3 genotype. The vaccine coverage in the Greek population was 90 %; however, the study population expressed complete coverage in 2 out of 264 infants (0–11 months) and in 20 out of 36 children (1–14 years). Roma and immigrant minorities represent 7 % of the Greek population, but make up 50 % of the study population, indicating a low vaccine coverage among these groups. Conclusions The B. pertussis MT27 and ptxP3 genotype is dominant in Greek, Roma and immigrant infants and children hospitalized in Greece. Thus, the predominant MLVA genotype in Greece is similar to other countries using acellular vaccines. PMID:29458550

Molecular epidemiology of Bordetella pertussis in the Philippines in 2012-2014.

PubMed

Galit, Salvacion Rosario L; Otsuka, Nao; Furuse, Yuki; Almonia, Daryl Joy V; Sombrero, Lydia T; Capeding, Rosario Z; Lupisan, Socorro P; Saito, Mariko; Oshitani, Hitoshi; Hiramatsu, Yukihiro; Shibayama, Keigo; Kamachi, Kazunari

2015-06-01

The present study was designed to determine the genotypes of circulating Bordetella pertussis in the Philippines by direct molecular typing of clinical specimens. Nasopharyngeal swabs (NPSs) were collected from 50 children hospitalized with pertussis in three hospitals during 2012-2014. Multilocus variable-number tandem repeat analysis (MLVA) was performed on the DNA extracts from NPSs. B. pertussis virulence-associated allelic genes (ptxA, prn, and fim3) and the pertussis toxin promoter, ptxP, were also investigated by DNA sequence-based typing. Twenty-six DNA extracts yielded a complete MLVA profile, which were sorted into 10 MLVA types. MLVA type 34 (MT34), which is rare in Australia, Europe, Japan, and the USA, was the predominant strain (50%). Seven MTs (MT29, MT32, MT33, and MT283-286, total 42%) were single-locus variants of MT34, while two (MT141 and MT287, total 8%) were double-locus variants of MT34. All MTs had the combination of virulence-associated allelic genes, ptxP1-ptxA1-prn1-fim3A. The B. pertussis population in the Philippines comprises genetically related strains. These strains are markedly different from those found in patients from other countries where acellular pertussis vaccines are used. The differences in vaccine types between these other countries and the Philippines, where the whole-cell vaccine is still used, may select for distinct populations of B. pertussis. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Use of multiple locus variable number tandem repeats analysis for the Brucella systematization].

PubMed

Kulakov, Iu K; Kovalev, D A; Misetova, E N; Golovneva, S I; Liapustina, L V; Zheludkov, M M

2012-01-01

The methods of molecular-genetic differentiation to strain level acquire increasing significance in the current system of struggle with brucellosis. MLVA (multiple locus variable number tandem repeats analysis) was selected for molecular-genetic differentiation to strain level and simultaneous establishment of the genetic relationship of investigated Brucella strains. The goal of this work was MLVA typing of three pathogenic Brucella species strains with the analysis of stability of chosen loci, discrimination power and concordance to conventional phenotypic methods of the Brucella differentiation for use in systematization of brucellosis causing agents. Twenty six Brucella strains representing reference (n = 15), vaccine (n = 2) and field strains of three pathogenic Brucella species were tested: B. melitensis (n = 3), B. abortus (n = 2), B. suis (n = 2), and isolates (n = 2) with unidentified taxonomic position using MLVA with 9 pairs primers on known variable loci of Brucella genome. The analysis of the stability of chosen loci, discrimination power on Hunter-Gaston discrimination index (HGDI) and consistency to phenotypic methods of identification was performed. MLVA was confirmed for the results of phenotypic methods of identification, stability of the chosen loci in majority reference, and vaccine strains with a high index of variability HGDI 0.9969 for all loci. A dendrogram was plotted on the basis of MLVA data on distributed Brucella strains in related clusters according to its taxonomic species and biovar positions and construction of 25 genotypes. B. melitensis strains formed cluster related to the reference strain of B. melitensis 63/9 biovar 2. Australian isolates of Brucella 83-4 and Brucella 83-6 isolated from rodents formed a cluster distant from other strains of Brucella. MLVA is a promising method for differentiation of Brucella strains with known and unresolved taxonomic status for their systematization and creation of MLVA genotype catalogue that will promote qualitative improvement of brucellosis surveillance system in Russia.

Subtyping of Canadian isolates of Salmonella Enteritidis using Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) alone and in combination with Pulsed-Field Gel Electrophoresis (PFGE) and phage typing.

PubMed

Ziebell, Kim; Chui, Linda; King, Robin; Johnson, Suzanne; Boerlin, Patrick; Johnson, Roger P

2017-08-01

Salmonella enterica subspecies enterica serovar Enteritidis (SE) is one of the most common causes of human salmonellosis and in Canada currently accounts for over 40% of human cases. Reliable subtyping of isolates is required for outbreak detection and source attribution. However, Pulsed-Field Gel Electrophoresis (PFGE), the current standard subtyping method for Salmonella spp., is compromised by the high genetic homogeneity of SE. Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) was introduced to supplement PFGE, although there is a lack of data on the ability of MLVA to subtype Canadian isolates of SE. Three subtyping methods, PFGE, MLVA and phage typing were compared for their discriminatory power when applied to three panels of Canadian SE isolates: Panel 1: 70 isolates representing the diversity of phage types (PTs) and PFGE subtypes within these PTs; Panel 2: 214 apparently unrelated SE isolates of the most common PTs; and Panel 3: 27 isolates from 10 groups of epidemiologically related strains. For Panel 2 isolates, four MLVA subtypes were shared among 74% of unrelated isolates and in Panel 3 isolates, one MLVA subtype accounted for 62% of the isolates. For all panels, combining results from PFGE, MLVA and PT gave the best discrimination, except in Panel 1, where the combination of PT and PFGE was equally as high, due to the selection criteria for this panel. However, none of these methods is sufficiently discriminatory alone for reliable outbreak detection or source attribution, and must be applied together to achieve sufficient discrimination for practical purposes. Even then, some large clusters were not differentiated adequately. More discriminatory methods are required for reliable subtyping of this genetically highly homogeneous serovar. This need will likely be met by whole genome sequence analysis given the recent promising reports and as more laboratories implement this tool for outbreak response and surveillance. Copyright © 2017 Elsevier B.V. All rights reserved.

[Multiple-locus variable number tandem repeat analysis of Bordetella pertussis strains collected in the Czech Republic in 1967-2015: spread of a variant adapted to the population with a high vaccination coverage].

PubMed

Lžičařová, D; Zavadilová, J; Musílek, M; Jandová, Z; Křížová, P; Fabiánová, K

To perform multiple-locus variable number tandem repeat analysis (MLVA) of B. pertussis strains from the collection of the National Reference Laboratory for Diphtheria and Pertussis (NRL/DIPE), National Institute of Public Health (NIPH), Prague. The study strains were isolated from clinical specimens collected mostly in the Czech Republic over a nearly 50-year period from 1967 to 2015 (June). The isolates from three periods characterized by different vaccination strategies and trends in pertussis are compared for genetic diversity and distribution of MLVA types (MT). Based on the results obtained, the suitability for use of MLVA in the analysis of epidemic outbreaks of B. pertussis in the Czech Republic is considered. DNA samples extracted from B. pertussis strains included in the present study were examined by MLVA using the standard protocol. Data were processed by means of the eBURST algorithm and the calculation of the Simpson diversity index (DI) was used for the statistical analysis. Data were analyzed as a whole and also separately for strains from the three periods: 1967-1980, 1990-2007, and 2008-2015 (June). Fourteen different MT were detected in the study strains, with three of them not being reported before. The most common MTs were MT27 and MT29. MT29 was predominant in 1967-1980 while MT27 was the most prevalent in 1990-2007 and 2008-2015 (June). The DI was the lowest (0.49) in 2008-2015 (June), and comparably higher DIs were calculated for the two previous periods (i.e. 0.667 for 1967-1980 and 0.654 for 1990-2007). MLVA revealed a decrease in genetic diversity and shifts in MT distribution of B. pertussis strains isolated from clinical specimens in the Czech Republic from 1967 to 2015 (June). These shifts in the Czech Republic can be characterized as a progressive increase in global MTs at the expense of the locally unique ones. The most common MT, similarly to other geographical areas with long-term high vaccination coverage, is MT27. The results of MLVA of 136 B. pertussis strains can provide a background for using this method in molecular epidemiological analysis of smaller groups of strains.

Comparison of four molecular methods to type Salmonella Enteritidis strains.

PubMed

Campioni, Fábio; Pitondo-Silva, André; Bergamini, Alzira M M; Falcão, Juliana P

2015-05-01

This study compared the pulsed-field gel electrophoresis (PFGE), enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR), multilocus variable-number of tanden-repeat analysis (MLVA), and multilocus sequence typing (MLST) methods for typing 188 Salmonella Enteritidis strains from different sources isolated over a 24-year period in Brazil. PFGE and ERIC-PCR were more efficient than MLVA for subtyping the strains. However, MLVA provided additional epidemiological information for those strains. In addition, MLST showed the Brazilian strains as belonging to the main clonal complex of S. Enteritidis, CC11, and provided the first report of two new STs in the S. enterica database but could not properly subtype the strains. Our results showed that the use of PFGE or ERIC-PCR together with MLVA is suitable to efficiently subtype S. Enteritidis strains and provide important epidemiological information. © 2015 APMIS. Published by John Wiley & Sons Ltd.

Comparison of 2 proposed MLVA protocols for subtyping non-O157:H7 verotoxigenic Escherichia coli.

PubMed

González, Juliana; Sanso, Andrea Mariel; Lucchesi, Paula María Alejandra; Bustamante, Ana Victoria

2014-04-01

Multiple locus variable number tandem repeats (VNTRs) analysis (MLVA) has become a reliable tool, able to establish genetic relationships for epidemiological surveillance and molecular subtyping of pathogens such as verotoxigenic Escherichia coli (VTEC). This emerging pathogen whose primary reservoir is the cattle causes severe disease in humans, such as hemorrhagic colitis and hemolytic uremic syndrome. With the aim of comparing a recently proposed MLVA assay with that used routinely in our laboratory, we analyzed a set of VTEC isolates (n = 72) obtained from meat using both assays. All samples could be typed by the new MLVA assay, and an increase in the number of distinct profiles (31-43) was observed. However, intraserotype resolution was not significantly enhanced; thus, the incorporation of more VNTR loci is still needed to achieve a greater discrimination among non-O157:H7 serotypes. Copyright © 2014 Elsevier Inc. All rights reserved.

Inter-laboratory comparison of multi-locus variable-number tandem repeat analysis (MLVA) for verocytotoxin-producing Escherichia coli O157 to facilitate data sharing.

PubMed

Holmes, A; Perry, N; Willshaw, G; Hanson, M; Allison, L

2015-01-01

Multi-locus variable number tandem repeat analysis (MLVA) is used in clinical and reference laboratories for subtyping verocytotoxin-producing Escherichia coli O157 (VTEC O157). However, as yet there is no common allelic or profile nomenclature to enable laboratories to easily compare data. In this study, we carried out an inter-laboratory comparison of an eight-loci MLVA scheme using a set of 67 isolates of VTEC O157. We found all but two isolates were identical in profile in the two laboratories, and repeat units were homogeneous in size but some were incomplete. A subset of the isolates (n = 17) were sequenced to determine the actual copy number of representative alleles, thereby enabling alleles to be named according to international consensus guidelines. This work has enabled us to realize the potential of MLVA as a portable, highly discriminatory and convenient subtyping method.

MULTIPLE-LOCUS VARIABLE-NUMBER TANDEM REPEAT ANALYSIS OF BRUCELLA ISOLATES FROM THAILAND.

PubMed

Kumkrong, Khurawan; Chankate, Phanita; Tonyoung, Wittawat; Intarapuk, Apiradee; Kerdsin, Anusak; Kalambaheti, Thareerat

2017-01-01

Brucellosis-induced abortion can result in significant economic loss to farm animals. Brucellosis can be transmitted to humans during slaughter of infected animals or via consumption of contaminated food products. Strain identification of Brucella isolates can reveal the route of transmission. Brucella strains were isolated from vaginal swabs of farm animal, cow milk and from human blood cultures. Multiplex PCR was used to identify Brucella species, and owing to high DNA homology among Brucella isolates, multiple-locus variable-number tandem repeat analysis (MLVA) based on the number of tandem repeats at 16 different genomic loci was used for strain identification. Multiplex PCR categorized the isolates into B. abortus (n = 7), B. melitensis (n = 37), B. suis (n = 3), and 5 of unknown Brucella spp. MLVA-16 clustering analysis differentiated the strains into various genotypes, with Brucella isolates from the same geographic region being closely related, and revealed that the Thai isolates were phylogenetically distinct from those in other countries, including within the Southeast Asian region. Thus, MLVA-16 typing has utility in epidemiological studies.

Evaluating the Use of Multilocus Variable Number Tandem Repeat Analysis of Shiga Toxin-Producing Escherichia coli O157 as a Routine Public Health Tool in England

PubMed Central

Byrne, Lisa; Elson, Richard; Dallman, Timothy J.; Perry, Neil; Ashton, Philip; Wain, John; Adak, Goutam K.; Grant, Kathie A.; Jenkins, Claire

2014-01-01

Multilocus variable number tandem repeat analysis (MLVA) provides microbiological support for investigations of clusters of cases of infection with Shiga toxin-producing E. coli (STEC) O157. All confirmed STEC O157 isolated in England and submitted to the Gastrointestinal Bacteria Reference Unit (GBRU) during a six month period were typed using MLVA, with the aim of assessing the impact of this approach on epidemiological investigations. Of 539 cases investigated, 341 (76%) had unique (>2 single locus variants) MLVA profiles, 12% of profiles occurred more than once due to known household transmission and 12% of profiles occurred as part of 41 clusters, 21 of which were previously identified through routine public health investigation of cases. The remaining 20 clusters were not previously detected and STEC enhanced surveillance data for associated cases were retrospectively reviewed for epidemiological links including shared exposures, geography and/or time. Additional evidence of a link between cases was found in twelve clusters. Compared to phage typing, the number of sporadic cases was reduced from 69% to 41% and the diversity index for MLVA was 0.996 versus 0.782 for phage typing. Using MLVA generates more data on the spatial and temporal dispersion of cases, better defining the epidemiology of STEC infection than phage typing. The increased detection of clusters through MLVA typing highlights the challenges to health protection practices, providing a forerunner to the advent of whole genome sequencing as a diagnostic tool. PMID:24465775

Genetic diversity of O157:H7 and non-O157 verocytotoxigenic Escherichia coli from Argentina inferred from multiple-locus variable-number tandem repeat analysis (MLVA).

PubMed

Bustamante, Ana V; Sanso, A Mariel; Lucchesi, Paula M A; Parma, Alberto E

2010-04-01

Although serotype O157:H7 has been implicated in most cases of haemolytic-uraemic syndrome (HUS), there is growing concern about non-O157 serotypes of verocytotoxigenic Escherichia coli (VTEC). Multiple-locus variable-number tandem repeat analysis (MLVA) has been focused on the specific typing of O157:H7 isolates, but recently, a generic MLVA assay for E. coli and Shigella has been developed. We performed a study of the polymorphism in 7 generic VNTR loci both in VTEC O157:H7 and non-O157 isolates from Argentina, in order to asses the ability of the method to type this group of isolates and to get insight into their genetic diversity. Sixty-four isolates from cattle, patients with diarrhoea, and contaminated food belonging to 8 different serotypes were studied. All of them could be typed by this method and revealed 41 different MLVA genotypes. The MLVA dendrogram showed 2 main clusters which corresponded to O157:H7 and non-O157, respectively. Our results confirm the suitability of this MLVA method for analyzing VTEC isolates belonging to several serotypes, both O157:H7 as well as non-O157, highlight the genetic variability of the O157:H7 serotype and the need of additional research in order to find more VNTR loci that could allow a higher discrimination among non-O157 VTEC. (c) 2009 Elsevier GmbH. All rights reserved.

Evaluating the use of multilocus variable number tandem repeat analysis of Shiga toxin-producing Escherichia coli O157 as a routine public health tool in England.

PubMed

Byrne, Lisa; Elson, Richard; Dallman, Timothy J; Perry, Neil; Ashton, Philip; Wain, John; Adak, Goutam K; Grant, Kathie A; Jenkins, Claire

2014-01-01

Multilocus variable number tandem repeat analysis (MLVA) provides microbiological support for investigations of clusters of cases of infection with Shiga toxin-producing E. coli (STEC) O157. All confirmed STEC O157 isolated in England and submitted to the Gastrointestinal Bacteria Reference Unit (GBRU) during a six month period were typed using MLVA, with the aim of assessing the impact of this approach on epidemiological investigations. Of 539 cases investigated, 341 (76%) had unique (>2 single locus variants) MLVA profiles, 12% of profiles occurred more than once due to known household transmission and 12% of profiles occurred as part of 41 clusters, 21 of which were previously identified through routine public health investigation of cases. The remaining 20 clusters were not previously detected and STEC enhanced surveillance data for associated cases were retrospectively reviewed for epidemiological links including shared exposures, geography and/or time. Additional evidence of a link between cases was found in twelve clusters. Compared to phage typing, the number of sporadic cases was reduced from 69% to 41% and the diversity index for MLVA was 0.996 versus 0.782 for phage typing. Using MLVA generates more data on the spatial and temporal dispersion of cases, better defining the epidemiology of STEC infection than phage typing. The increased detection of clusters through MLVA typing highlights the challenges to health protection practices, providing a forerunner to the advent of whole genome sequencing as a diagnostic tool.

On-line resources for bacterial micro-evolution studies using MLVA or CRISPR typing.

PubMed

Grissa, Ibtissem; Bouchon, Patrick; Pourcel, Christine; Vergnaud, Gilles

2008-04-01

The control of bacterial pathogens requires the development of tools allowing the precise identification of strains at the subspecies level. It is now widely accepted that these tools will need to be DNA-based assays (in contrast to identification at the species level, where biochemical based assays are still widely used, even though very powerful 16S DNA sequence databases exist). Typing assays need to be cheap and amenable to the designing of international databases. The success of such subspecies typing tools will eventually be measured by the size of the associated reference databases accessible over the internet. Three methods have shown some potential in this direction, the so-called spoligotyping assay (Mycobacterium tuberculosis, 40,000 entries database), Multiple Loci Sequence Typing (MLST; up to a few thousands entries for the more than 20 bacterial species), and more recently Multiple Loci VNTR Analysis (MLVA; up to a few hundred entries, assays available for more than 20 pathogens). In the present report we will review the current status of the tools and resources we have developed along the past seven years to help in the setting-up or the use of MLVA assays or lately for analysing Clustered Regularly Interspaced Short Palindromic Repeats called CRISPRs which are the basis for spoligotyping assays.

Phylogeography and population structure of the biologically invasive phytopathogen Erwinia amylovora inferred using minisatellites.

PubMed

Bühlmann, Andreas; Dreo, Tanja; Rezzonico, Fabio; Pothier, Joël F; Smits, Theo H M; Ravnikar, Maja; Frey, Jürg E; Duffy, Brion

2014-07-01

Erwinia amylovora causes a major disease of pome fruit trees worldwide, and is regulated as a quarantine organism in many countries. While some diversity of isolates has been observed, molecular epidemiology of this bacterium is hindered by a lack of simple molecular typing techniques with sufficiently high resolution. We report a molecular typing system of E. amylovora based on variable number of tandem repeats (VNTR) analysis. Repeats in the E. amylovora genome were identified with comparative genomic tools, and VNTR markers were developed and validated. A Multiple-Locus VNTR Analysis (MLVA) was applied to E. amylovora isolates from bacterial collections representing global and regional distribution of the pathogen. Based on six repeats, MLVA allowed the distinction of 227 haplotypes among a collection of 833 isolates of worldwide origin. Three geographically separated groups were recognized among global isolates using Bayesian clustering methods. Analysis of regional outbreaks confirmed presence of diverse haplotypes but also high representation of certain haplotypes during outbreaks. MLVA analysis is a practical method for epidemiological studies of E. amylovora, identifying previously unresolved population structure within outbreaks. Knowledge of such structure can increase our understanding on how plant diseases emerge and spread over a given geographical region. © 2013 Society for Applied Microbiology and John Wiley & Sons Ltd.

Molecular epidemiological characteristics of Salmonella enterica serovars Enteritidis, Typhimurium and Livingstone strains isolated in a Tunisian university hospital.

PubMed

Ktari, Sonia; Ksibi, Boutheina; Gharsallah, Houda; Mnif, Basma; Maalej, Sonda; Rhimi, Fouzia; Hammami, Adnene

2016-03-01

Enteritidis, Typhimurium and Livingstone are the main Salmonella enterica serovars recovered in Tunisia. Here, we aimed to assess the genetic diversity of fifty-seven Salmonella enterica strains from different sampling periods, origins and settings using pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and multi-locus variable-number tandem repeat analysis (MLVA). Salmonella Enteritidis, isolated from human and food sources from two regions in Sfax in 2007, were grouped into one cluster using PFGE. However, using MLVA these strains were divided into two clusters. Salmonella Typhimurium strains, recovered in 2012 and represent sporadic cases of human clinical isolates, were included in one PFGE cluster. Nevertheless, the MLVA technique, divided Salmonella Typhimurium isolates into six clusters with diversity index reaching (DI = 0.757). For Salmonella Livingstone which was responsible of two nosocomial outbreaks during 2000-2003, the PFGE and MLVA methods showed that these strains were genetically closely related. Salmonella Enteritidis and Salmonella Livingstone populations showed a single ST lineage ST11 and ST543 respectively. For Salmonella Typhimurium, two MLST sequence types ST19 and ST328 were defined. Salmonella Enteritidis and Salmonella Typhimurium strains were clearly differentiated by MLVA which was not the case using PFGE. © 2015 APMIS. Published by John Wiley & Sons Ltd.

Origin of the Outbreak in France of Pseudomonas syringae pv. actinidiae Biovar 3, the Causal Agent of Bacterial Canker of Kiwifruit, Revealed by a Multilocus Variable-Number Tandem-Repeat Analysis

PubMed Central

Cunty, A.; Cesbron, S.; Poliakoff, F.; Jacques, M.-A.

2015-01-01

The first outbreaks of bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae biovar 3 were detected in France in 2010. P. syringae pv. actinidiae causes leaf spots, dieback, and canker that sometimes lead to the death of the vine. P. syringae pv. actinidifoliorum, which is pathogenic on kiwi as well, causes only leaf spots. In order to conduct an epidemiological study to track the spread of the epidemics of these two pathogens in France, we developed a multilocus variable-number tandem-repeat (VNTR) analysis (MLVA). MLVA was conducted on 340 strains of P. syringae pv. actinidiae biovar 3 isolated in Chile, China, France, Italy, and New Zealand and on 39 strains of P. syringae pv. actinidifoliorum isolated in Australia, France, and New Zealand. Eleven polymorphic VNTR loci were identified in the genomes of P. syringae pv. actinidiae biovar 3 ICMP 18744 and of P. syringae pv. actinidifoliorum ICMP 18807. MLVA enabled the structuring of P. syringae pv. actinidiae biovar 3 and P. syringae pv. actinidifoliorum strains in 55 and 16 haplotypes, respectively. MLVA and discriminant analysis of principal components revealed that strains isolated in Chile, China, and New Zealand are genetically distinct from P. syringae pv. actinidiae strains isolated in France and in Italy, which appear to be closely related at the genetic level. In contrast, no structuring was observed for P. syringae pv. actinidifoliorum. We developed an MLVA scheme to explore the diversity within P. syringae pv. actinidiae biovar 3 and to trace the dispersal routes of epidemic P. syringae pv. actinidiae biovar 3 in Europe. We suggest using this MLVA scheme to trace the dispersal routes of P. syringae pv. actinidiae at a global level. PMID:26209667

Relationship between Distinct African Cholera Epidemics Revealed via MLVA Haplotyping of 337 Vibrio cholerae Isolates.

PubMed

Moore, Sandra; Miwanda, Berthe; Sadji, Adodo Yao; Thefenne, Hélène; Jeddi, Fakhri; Rebaudet, Stanislas; de Boeck, Hilde; Bidjada, Bawimodom; Depina, Jean-Jacques; Bompangue, Didier; Abedi, Aaron Aruna; Koivogui, Lamine; Keita, Sakoba; Garnotel, Eric; Plisnier, Pierre-Denis; Ruimy, Raymond; Thomson, Nicholas; Muyembe, Jean-Jacques; Piarroux, Renaud

2015-01-01

Since cholera appeared in Africa during the 1970s, cases have been reported on the continent every year. In Sub-Saharan Africa, cholera outbreaks primarily cluster at certain hotspots including the African Great Lakes Region and West Africa. In this study, we applied MLVA (Multi-Locus Variable Number Tandem Repeat Analysis) typing of 337 Vibrio cholerae isolates from recent cholera epidemics in the Democratic Republic of the Congo (DRC), Zambia, Guinea and Togo. We aimed to assess the relationship between outbreaks. Applying this method, we identified 89 unique MLVA haplotypes across our isolate collection. MLVA typing revealed the short-term divergence and microevolution of these Vibrio cholerae populations to provide insight into the dynamics of cholera outbreaks in each country. Our analyses also revealed strong geographical clustering. Isolates from the African Great Lakes Region (DRC and Zambia) formed a closely related group, while West African isolates (Togo and Guinea) constituted a separate cluster. At a country-level scale our analyses revealed several distinct MLVA groups, most notably DRC 2011/2012, DRC 2009, Zambia 2012 and Guinea 2012. We also found that certain MLVA types collected in the DRC persisted in the country for several years, occasionally giving rise to expansive epidemics. Finally, we found that the six environmental isolates in our panel were unrelated to the epidemic isolates. To effectively combat the disease, it is critical to understand the mechanisms of cholera emergence and diffusion in a region-specific manner. Overall, these findings demonstrate the relationship between distinct epidemics in West Africa and the African Great Lakes Region. This study also highlights the importance of monitoring and analyzing Vibrio cholerae isolates.

Variable Number of Tandem Repeats in Salmonella enterica subsp. enterica for Typing Purposes

PubMed Central

Ramisse, Vincent; Houssu, Perrine; Hernandez, Eric; Denoeud, France; Hilaire, Valérie; Lisanti, Olivier; Ramisse, Françoise; Cavallo, Jean-Didier; Vergnaud, Gilles

2004-01-01

The genomic sequences of Salmonella enterica subsp. enterica strains CT18, Ty2 (serovar Typhi), and LT2 (serovar Typhimurium) were analyzed for potential variable number tandem repeats (VNTRs). A multiple-locus VNTR analysis (MLVA) of 99 strains of S. enterica supsp. enterica based on 10 VNTRs distinguished 52 genotypes and placed them into four groups. All strains tested were independent human isolates from France and did not reflect isolates from outbreak episodes. Of these 10 VNTRs, 7 showed variability within serovar Typhi, whereas 1 showed variability within serovar Typhimurium. Four VNTRs showed high Nei's diversity indices (DIs) of 0.81 to 0.87 within serovar Typhi (n = 27). Additionally, three of these more variable VNTRs showed DIs of 0.18 to 0.58 within serovar Paratyphi A (n = 10). The VNTR polymorphic site within multidrug-resistant (MDR) serovar Typhimurium isolates (n = 39; resistance to ampicillin, chloramphenicol, spectinomycin, sulfonamides, and tetracycline) showed a DI of 0.81. Cluster analysis not only identified three genetically distinct groups consistent with the present serovar classification of salmonellae (serovars Typhi, Paratyphi A, and Typhimurium) but also discriminated 25 subtypes (93%) within serovar Typhi isolates. The analysis discriminated only eight subtypes within serovar Typhimurium isolates resistant to ampicillin, chloramphenicol, spectinomycin, sulfonamides, and tetracycline, possibly reflecting the emergence in the mid-1990s of the DT104 phage type, which often displays such an MDR spectrum. Coupled with the ongoing improvements in automated procedures offered by capillary electrophoresis, use of these markers is proposed in further investigations of the potential of MLVA in outbreaks of salmonellosis, especially outbreaks of typhoid fever. PMID:15583305

Genotypes of pathogenic Leptospira spp isolated from rodents in Argentina

PubMed Central

Loffler, Sylvia Grune; Pavan, Maria Elisa; Vanasco, Bibiana; Samartino, Luis; Suarez, Olga; Auteri, Carmelo; Romero, Graciela; Brihuega, Bibiana

2014-01-01

Leptospirosis is the most widespread zoonosis in the world and significant efforts have been made to determine and classify pathogenic Leptospira strains. This zoonosis is maintained in nature through chronic renal infections of carrier animals, with rodents and other small mammals serving as the most important reservoirs. Additionally, domestic animals, such as livestock and dogs, are significant sources of human infection. In this study, a multiple-locus variable-number tandem repeat analysis (MLVA) was applied to genotype 22 pathogenic Leptospira strains isolated from urban and periurban rodent populations from different regions of Argentina. Three MLVA profiles were identified in strains belonging to the species Leptospira interrogans (serovars Icterohaemorrhagiae and Canicola); one profile was observed in serovar Icterohaemorrhagiae and two MLVA profiles were observed in isolates of serovars Canicola and Portlandvere. All strains belonging to Leptospira borgpetersenii serovar Castellonis exhibited the same MLVA profile. Four different genotypes were isolated from urban populations of rodents, including both mice and rats and two different genotypes were isolated from periurban populations. PMID:24676656

Identification and typing of Brucella spp. in stranded harbour porpoises (Phocoena phocoena) on the Dutch coast.

PubMed

Maio, Elisa; Begeman, Lineke; Bisselink, Yvette; van Tulden, Peter; Wiersma, Lidewij; Hiemstra, Sjoukje; Ruuls, Robin; Gröne, Andrea; Roest, Hendrik-Ido-Jan; Willemsen, Peter; van der Giessen, Joke

2014-09-17

The presence of Brucella (B.) spp. in harbour porpoises stranded between 2008 and 2011 along the Dutch coast was studied. A selection of 265 tissue samples from 112 animals was analysed using conventional and molecular methods. In total, 4.5% (5/112) of the animals corresponding with 2.3% (6/265) Brucella positive tissue samples were Brucella positive by culture and these were all confirmed by real-time polymerase chain reaction (real-time PCR) based on the insertion element 711 (IS711). In addition, two more Brucella-positive tissue samples from two animals collected in 2011 were identified using real-time PCR resulting in an overall Brucella prevalence of 6.3% (7/112 animals). Brucella spp. were obtained from lungs (n=3), pulmonary lymph node (n=3) and lungworms (n=2). Multi Locus Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) typing based on the MLVA-16 showed that the Brucella isolates were B. ceti. Additional in silico Multi Locus Sequence typing (MLST) after whole genome sequencing of the 6 Brucella isolates confirmed B. ceti ST 23. According to the Brucella 2010 MLVA database, the isolated Brucella strains encountered were of five genotypes, in two distinct subclusters divided in two different time periods of harbour porpoises collection. This study is the first population based analyses for Brucella spp. infections in cetaceans stranded along the Dutch coast. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Effective application of multiple locus variable number of tandem repeats analysis to tracing Staphylococcus aureus in food-processing environment.

PubMed

Rešková, Z; Koreňová, J; Kuchta, T

2014-04-01

A total of 256 isolates of Staphylococcus aureus were isolated from 98 samples (34 swabs and 64 food samples) obtained from small or medium meat- and cheese-processing plants in Slovakia. The strains were genotypically characterized by multiple locus variable number of tandem repeats analysis (MLVA), involving multiplex polymerase chain reaction (PCR) with subsequent separation of the amplified DNA fragments by an automated flow-through gel electrophoresis. With the panel of isolates, MLVA produced 31 profile types, which was a sufficient discrimination to facilitate the description of spatial and temporal aspects of contamination. Further data on MLVA discrimination were obtained by typing a subpanel of strains by multiple locus sequence typing (MLST). MLVA coupled to automated electrophoresis proved to be an effective, comparatively fast and inexpensive method for tracing S. aureus contamination of food-processing factories. Subspecies genotyping of microbial contaminants in food-processing factories may facilitate identification of spatial and temporal aspects of the contamination. This may help to properly manage the process hygiene. With S. aureus, multiple locus variable number of tandem repeats analysis (MLVA) proved to be an effective method for the purpose, being sufficiently discriminative, yet comparatively fast and inexpensive. The application of automated flow-through gel electrophoresis to separation of DNA fragments produced by multiplex PCR helped to improve the accuracy and speed of the method. © 2013 The Society for Applied Microbiology.

Multiple-Locus VNTR Analysis (MLVA) for Bacterial Strain Identification - Quarterly Progress Report for the period 7/1/00 to 10/30/00

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dr. Paul Keim

2000-11-07

Multiple locus VNTR analysis (MLVA) systems are being developed for B. anthracis, Y. pestis and F. tularensis. These are high resolution DNA fingerprinting systems that will allow for molecular epidemiology and forensic analysis of these pathogens.

Multiple-Locus VNTR Analysis (MLVA) for Bacterial Strain Identification - Quarterly Progress Report for the Period 4/1/00 to 6/30/00

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dr. Paul Keim

2000-11-07

Multiple locus VNTR analysis (MLVA) systems are being developed for B. anthracis, Y. pestis and F. tularensis. These are high resolution DNA fingerprinting systems that will allow for molecular epidemiology and forensic analysis of these pathogens.

Clonal structure in Ichthyobacterium seriolicida, the causative agent of bacterial haemolytic jaundice in yellowtail, Seriola quinqueradiata, inferred from molecular epidemiological analysis.

PubMed

Matsuyama, T; Fukuda, Y; Sakai, T; Tanimoto, N; Nakanishi, M; Nakamura, Y; Takano, T; Nakayasu, C

2017-08-01

Bacterial haemolytic jaundice caused by Ichthyobacterium seriolicida has been responsible for mortality in farmed yellowtail, Seriola quinqueradiata, in western Japan since the 1980s. In this study, polymorphic analysis of I. seriolicida was performed using three molecular methods: amplified fragment length polymorphism (AFLP) analysis, multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA). Twenty-eight isolates were analysed using AFLP, while 31 isolates were examined by MLST and MLVA. No polymorphisms were identified by AFLP analysis using EcoRI and MseI, or by MLST of internal fragments of eight housekeeping genes. However, MLVA revealed variation in repeat numbers of three elements, allowing separation of the isolates into 16 sequence types. The unweighted pair group method using arithmetic averages cluster analysis of the MLVA data identified four major clusters, and all isolates belonged to clonal complexes. It is likely that I. seriolicida populations share a common ancestor, which may be a recently introduced strain. © 2016 John Wiley & Sons Ltd.

Molecular characterization of Shiga-toxigenic Escherichia coli isolated from diverse sources from India by multi-locus variable number tandem repeat analysis (MLVA).

PubMed

Kumar, A; Taneja, N; Sharma, R K; Sharma, H; Ramamurthy, T; Sharma, M

2014-12-01

In a first study from India, a diverse collection of 140 environmental and clinical non-O157 Shiga-toxigenic Escherichia coli strains from a large geographical area in north India was typed by multi-locus variable number tandem repeat analysis (MLVA). The distribution of major virulence genes stx1, stx2 and eae was found to be 78%, 70% and 10%, respectively; 15 isolates were enterohaemorrhagic E. coli (stx1 +/stx2 + and eae +). By MLVA analysis, 44 different alleles were obtained. Dendrogram analysis revealed 104 different genotypes and 19 MLVA-type complexes divided into two main lineages, i.e. mutton and animal stool. Human isolates presented a statistically significant greater odds ratio for clustering with mutton samples compared to animal stool isolates. Five human isolates clustered with animal stool strains suggesting that some of the human infections may be from cattle, perhaps through milk, contact or the environment. Further epidemiological studies are required to explore these sources in context with occurrence of human cases.

Locus-specific mutational events in a multilocus variable-number tandem repeat analysis of Escherichia coli O157:H7.

PubMed

Noller, Anna C; McEllistrem, M Catherine; Shutt, Kathleen A; Harrison, Lee H

2006-02-01

Multilocus variable-number tandem repeat analysis (MLVA) is a validated molecular subtyping method for detecting and evaluating Escherichia coli O157:H7 outbreaks. In a previous study, five outbreaks with a total of 21 isolates were examined by MLVA. Nearly 20% of the epidemiologically linked strains were single-locus variants (SLV) of their respective predominant outbreak clone. This result prompted an investigation into the mutation rates of the seven MLVA loci (TR1 to TR7). With an outbreak strain that was an SLV at the TR1 locus of the predominant clone, parallel and serial batch culture experiments were performed. In a parallel experiment, none (0/384) of the strains analyzed had mutations at the seven MLVA loci. In contrast, in the two 5-day serial experiments, 4.3% (41/960) of the strains analyzed had a significant variation in at least one of these loci (P < 0.001). The TR2 locus accounted for 85.3% (35/41) of the mutations, with an average mutation rate of 3.5 x 10(-3); the mutations rates for TR1 and TR5 were 10-fold lower. Single additions accounted for 77.1% (27/35) of the mutation events in TR2 and all (6/6) of the additions in TR1 and TR5. The remaining four loci had no slippage events detected. The mutation rates were locus specific and may impact the interpretation of MLVA data for epidemiologic investigations.

Origin of the Outbreak in France of Pseudomonas syringae pv. actinidiae Biovar 3, the Causal Agent of Bacterial Canker of Kiwifruit, Revealed by a Multilocus Variable-Number Tandem-Repeat Analysis.

PubMed

Cunty, A; Cesbron, S; Poliakoff, F; Jacques, M-A; Manceau, C

2015-10-01

The first outbreaks of bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae biovar 3 were detected in France in 2010. P. syringae pv. actinidiae causes leaf spots, dieback, and canker that sometimes lead to the death of the vine. P. syringae pv. actinidifoliorum, which is pathogenic on kiwi as well, causes only leaf spots. In order to conduct an epidemiological study to track the spread of the epidemics of these two pathogens in France, we developed a multilocus variable-number tandem-repeat (VNTR) analysis (MLVA). MLVA was conducted on 340 strains of P. syringae pv. actinidiae biovar 3 isolated in Chile, China, France, Italy, and New Zealand and on 39 strains of P. syringae pv. actinidifoliorum isolated in Australia, France, and New Zealand. Eleven polymorphic VNTR loci were identified in the genomes of P. syringae pv. actinidiae biovar 3 ICMP 18744 and of P. syringae pv. actinidifoliorum ICMP 18807. MLVA enabled the structuring of P. syringae pv. actinidiae biovar 3 and P. syringae pv. actinidifoliorum strains in 55 and 16 haplotypes, respectively. MLVA and discriminant analysis of principal components revealed that strains isolated in Chile, China, and New Zealand are genetically distinct from P. syringae pv. actinidiae strains isolated in France and in Italy, which appear to be closely related at the genetic level. In contrast, no structuring was observed for P. syringae pv. actinidifoliorum. We developed an MLVA scheme to explore the diversity within P. syringae pv. actinidiae biovar 3 and to trace the dispersal routes of epidemic P. syringae pv. actinidiae biovar 3 in Europe. We suggest using this MLVA scheme to trace the dispersal routes of P. syringae pv. actinidiae at a global level. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Genetic stability of Brucella abortus isolates from an outbreak by multiple-locus variable-number tandem repeat analysis (MLVA16)

PubMed Central

2014-01-01

Background Brucellosis caused by Brucella abortus is one of the most important zoonoses in the world. Multiple-locus variable-number tandem repeat analysis (MLVA16) has been shown be a useful tool to epidemiological traceback studies in B. abortus infection. Thus, the present study aimed (i) to evaluate the genetic diversity of B. abortus isolates from a brucellosis outbreak, and (ii) to investigate the in vivo stability of the MLVA16 markers. Results Three-hundred and seventy-five clinical samples, including 275 vaginal swabs and 100 milk samples, were cultured from a brucellosis outbreak in a cattle herd, which adopted RB51 vaccination and test-and-slaughter policies. Thirty-seven B. abortus isolates were obtained, eight from milk and twenty-nine from post-partum/abortion vaginal swabs, which were submitted to biotyping and genotyping by MLVA16. Twelve B. abortus isolates obtained from vaginal swabs were identified as RB51. Twenty four isolates, seven obtained from milk samples and seventeen from vaginal swabs, were identified as B. abortus biovar 3, while one isolate from vaginal swabs was identified as B. abortus biovar 1. Three distinct genotypes were observed during the brucellosis outbreak: RB observed in all isolates identified as RB51; W observed in all B. abortus biovar 3 isolates; and Z observed in the single B. abortus biovar 1 isolate. Epidemiological and molecular data show that the B. abortus biovar 1 genotype Z strain is not related to the B. abortus biovar 3 genotype W isolates, and represents a new introduction B. abortus during the outbreak. Conclusions The results of the present study on typing of multiple clinical B. abortus isolates from the same outbreak over a sixteen month period indicate the in vivo stability of MLVA16 markers, a low genetic diversity among B. abortus isolates and the usefulness of MLVA16 for epidemiological studies of bovine brucellosis. PMID:25015840

How do hospital professionals involved in a randomised controlled trial perceive the value of genotyping vs. PCR-ribotyping for control of hospital acquired C. difficile infections?

PubMed Central

2014-01-01

Background Despite scientific advances in typing of C. difficile strains very little is known about how hospital staff use typing results during periods of increased incidence (PIIs). This qualitative study, undertaken alongside a randomised controlled trial (RCT), explored this issue. The trial compared ribotyping versus more rapid genotyping (MLVA or multilocus variable repeat analysis) and found no significant difference in post 48 hour cases (C difficile transmissions). Methods In-depth qualitative interviews with senior staff in 11/16 hospital trusts in the trial (5 MLVA and 6 Ribotyping). Semi-structured interviews were conducted at end of the trial period. Transcripts were content analysed using framework analysis supported by NVivo-8 software. Common sub-themes were extracted by two researchers independently. These were compared and organised into over-arching categories or ‘super-ordinate themes’. Results The trial recorded that 45% of typing tests had some impact on infection control (IC) activities. Interviews indicated that tests had little impact on initial IC decisions. These were driven by hospital protocols and automatically triggered when a PII was identified. To influence decision-making, a laboratory turnaround time < 3 days (ideally 24 hours) was suggested; MLVA turnaround time was 5.3 days. Typing results were predominantly used to modify initiated IC activities such as ward cleaning, audits of practice or staff training; major decisions (e.g. ward closure) were unaffected. Organisational factors could limit utilisation of MLVA results. Results were twice as likely to be reported as ‘aiding management’ (indirect benefit) than impacting on IC activities (direct effect). Some interviewees considered test results provided reassurance about earlier IC decisions; others identified secondary benefits on organisational culture. An underlying benefit of improved discrimination provided by MLVA typing was the ability to explore epidemiology associated with CDI cases in a hospital more thoroughly. Conclusions Ribotyping and MLVA are both valued by users. MLVA had little additional direct impact on initial infection control decisions. This would require reduced turnaround time. The major impact is adjustments to earlier IC measures and retrospective reassurance. For this, turnaround time is less important than discriminatory power. The potential remains for wider use of genotyping to examine transmission routes. PMID:24656142

Tracing Staphylococcus aureus in small and medium-sized food-processing factories on the basis of molecular sub-species typing.

PubMed

Koreňová, Janka; Rešková, Zuzana; Véghová, Adriana; Kuchta, Tomáš

2015-01-01

Contamination by Staphylococcus aureus of the production environment of three small or medium-sized food-processing factories in Slovakia was investigated on the basis of sub-species molecular identification by multiple locus variable number of tandem repeats analysis (MLVA). On the basis of MLVA profiling, bacterial isolates were assigned to 31 groups. Data from repeated samplings over a period of 3 years facilitated to draw spatial and temporal maps of the contamination routes for individual factories, as well as identification of potential persistent strains. Information obtained by MLVA typing allowed to identify sources and routes of contamination and, subsequently, will allow to optimize the technical and sanitation measures to ensure hygiene.

Tuberculosis Caused by Mycobacterium orygis in Dairy Cattle and Captured Monkeys in Bangladesh: a New Scenario of Tuberculosis in South Asia.

PubMed

Rahim, Z; Thapa, J; Fukushima, Y; van der Zanden, A G M; Gordon, S V; Suzuki, Y; Nakajima, C

2017-12-01

Mycobacterium orygis, commonly known as the oryx bacillus and a newly proposed Mycobacterium tuberculosis complex subspecies, was isolated from 18 cattle in a dairy farm and two captured rhesus monkeys in a zoo in Bangladesh. All the infected animals had tuberculosis lesions in their lungs, suggesting transmission and infection with M. orygis by an airborne route. The 20 isolates were analysed using a range of conventional and molecular typing methods, and RD-deletion typing and sequencing of selected genes confirmed the isolates as M. orygis. Multiple-locus variable-number tandem repeat analysis (MLVA) allowed the isolates to be divided into three clusters based on the relatedness of their MLVA profiles. The two monkey isolates shared the same MLVA pattern with 15 of the cattle isolates, whereas the remaining three cattle isolates had different patterns, even though the latter animals had been kept in the same dairy farm. The diversity observed among isolates may suggest the bacteria have been established in this area for a long period. This study along with other recent findings that report the detection of M. orygis from animals as well as humans originating from South Asia potentially indicate endemic distribution of M. orygis in South Asia. © 2016 Blackwell Verlag GmbH.

Multiple-Locus Variable-Number Tandem Repeat Analysis of Dutch Bordetella pertussis Strains Reveals Rapid Genetic Changes with Clonal Expansion during the Late 1990s

PubMed Central

Schouls, Leo M.; van der Heide, Han G. J.; Vauterin, Luc; Vauterin, Paul; Mooi, Frits R.

2004-01-01

Bordetella pertussis, the causative agent of whooping cough, has remained endemic in The Netherlands despite extensive nationwide vaccination since 1953. In the 1990s, several epidemic periods have resulted in many cases of pertussis. We have proposed that strain variation has played a major role in the upsurges of this disease in The Netherlands. Therefore, molecular characterization of strains is important in identifying the causes of pertussis epidemiology. For this reason, we have developed a multiple-locus variable-number tandem repeat analysis (MLVA) typing system for B. pertussis. By combining the MLVA profile with the allelic profile based on multiple-antigen sequence typing, we were able to further differentiate strains. The relationships between the various genotypes were visualized by constructing a minimum spanning tree. MLVA of Dutch strains of B. pertussis revealed that the genotypes of the strains isolated in the prevaccination period were diverse and clearly distinct from the strains isolated in the 1990s. Furthermore, there was a decrease in diversity in the strains from the late 1990s, with a remarkable clonal expansion that coincided with the epidemic periods. Using this genotyping, we have been able to show that B. pertussis is much more dynamic than expected. PMID:15292152

Genetic diversity and antimicrobial resistance pattern of Salmonella enterica serovar Enteritidis clinical isolates in Thailand.

PubMed

Utrarachkij, Fuangfa; Nakajima, Chie; Siripanichgon, Kanokrat; Changkaew, Kanjana; Thongpanich, Yuwanda; Pornraungwong, Srirat; Suthienkul, Orasa; Suzuki, Yasuhiko

2016-04-01

To trace the history of antimicrobial resistance in Salmonella enterica serovar Enteritidis (S. Enteritidis, SE) circulating in Thailand, we characterised clinical isolates obtained during 2004-2007. Antimicrobial resistance profiles, multi-locus variable number tandem repeat analysis (MLVA) types and 3 representative virulence determinants (spvA, sodCI and sopE) were established from SE isolates (n = 192) collected from stool and blood of patients throughout Thailand during the period 2004-2007. Resistance was found in SE against 10 out of 11 antimicrobials studied. The highest resistance ratios were observed for nalidixic acid (83.2%), ciprofloxacin (51.1%) and ampicillin (50.5%), and 25.5% were multidrug resistant. Based on five polymorphic tandem repeat loci analysis, MLVA identified 20 distinct types with three closely related predominant types. A significant increase of AMP resistance from 2004 to 2006 was strongly correlated with that of a MLVA type, 5-5-11-7-3. The usage of antimicrobials in human medicine or farm settings might act as selective pressures and cause the spread of resistant strains. Hence, a strict policy on antimicrobial usage needs to be implemented to achieve the control of resistant SE in Thailand. Copyright © 2015 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Increase in Genetic Diversity of Haemophilus influenzae Serotype b (Hib) Strains after Introduction of Hib Vaccination in The Netherlands

PubMed Central

Schouls, Leo M.; van der Ende, Arie; van de Pol, Ingrid; Schot, Corrie; Spanjaard, Lodewijk; Vauterin, Paul; Wilderbeek, Dorus; Witteveen, Sandra

2005-01-01

Recently, there has been an increase in The Netherlands in the number of cases of invasive disease caused by Haemophilus influenzae serotype b (Hib). To study a possible change in the Hib population that could explain the rise in incidence, a multiple-locus variable number tandem repeats analysis (MLVA) was developed to genotype H. influenzae isolates. The MLVA enabled the differentiation of H. influenzae serotype b strains with higher discriminatory power than multilocus sequence typing (MLST). MLVA profiles of noncapsulated H. influenzae and H. influenzae serotype f strains were more heterogeneous than serotype b strains and were distinct from Hib, although some overlap occurred. The MLVA was used to genotype a collection of 520 H. influenzae serotype b strains isolated from patients in The Netherlands with invasive disease. The strains were collected from 1983 from 2002, covering a time period of 10 years before and 9 years after the introduction of the Hib vaccine in the Dutch national vaccination program. MLVA revealed a sharp increase in genetic diversity of Hib strains isolated from neonates to 4-year-old patients after 1993, when the Hib vaccine was introduced. Hib strains isolated from patients older than 4 years in age were genetically diverse, and no significant change in diversity was seen after the introduction of the vaccine. These observations suggest that after the introduction of the Hib vaccine young children no longer constitute the reservoir for Hib and that they are infected by adults carrying genetically diverse Hib strains. PMID:15956392

Evaluation of MLVA for epidemiological typing and outbreak detection of ESBL-producing Escherichia coli in Sweden.

PubMed

Helldal, Lisa; Karami, Nahid; Welinder-Olsson, Christina; Moore, Edward R B; Åhren, Christina

2017-01-06

To identify the spread of nosocomial infections and halt outbreak development caused by Escherichia coli that carry multiple antibiotic resistance factors, such as extended-spectrum beta-lactamases (ESBLs) and carbapenemases, is becoming demanding challenges due to the rapid global increase and constant and increasing influx of these bacteria from the community to the hospital setting. Our aim was to assess a reliable and rapid typing protocol for ESBL-E. coli, with the primary focus to screen for possible clonal relatedness between isolates. All clinical ESBL-E. coli isolates, collected from hospitals (n = 63) and the community (n = 41), within a single geographical region over a 6 months period, were included, as well as clinical isolates from a polyclonal outbreak (ST131, n = 9, and ST1444, n = 3). The sporadic cases represented 36 STs, of which eight STs dominated i.e. ST131 (n = 33 isolates), ST648 (n = 10), ST38 (n = 9), ST12 and 69 (each n = 4), ST 167, 405 and 372 (each n = 3). The efficacy of multiple-locus variable number tandem repeat analysis (MLVA) was evaluated using three, seven or ten loci, in comparison with that of pulsed-field gel electrophoresis (PFGE) and multi locus sequence typing (MLST). MLVA detected 39, 55 and 60 distinct types, respectively, using three (GECM-3), seven (GECM-7) or ten (GECM-10) loci. For GECM-7 and -10, 26 STs included one type and eleven STs each included several types, the corresponding numbers for GECM-3 were 29 and 8. The highest numbers were seen for ST131 (7,7 and 8 types, respectively), ST38 (5,5,8) and ST648 (4,5,5). Good concordance was observed with PFGE and GECM-7 and -10, despite fewer types being identified with MLVA; 78 as compared to 55 and 60 types. The lower discriminatory power of MLVA was primarily seen within the O25b-ST131 lineage (n = 34) and its H30-Rx subclone (n = 21). Epidemiologically unrelated O25b-ST131 isolates were clustered with O25b-ST131 outbreak isolates by MLVA, whereas the ST1444 outbreak isolates were accurately distinguished from unrelated isolates. MLVA, even when using only three loci, represents an easy initial typing tool for epidemiological screening of ESBL-E. coli. For the ST131-O25b linage, complementary methods may be needed to obtain sufficient resolution.

MLVA for Salmonella enterica subsp. enterica Serovar Dublin: Development of a Method Suitable for Inter-Laboratory Surveillance and Application in the Context of a Raw Milk Cheese Outbreak in France in 2012

PubMed Central

Vignaud, Marie-Léone; Cherchame, Emeline; Marault, Muriel; Chaing, Emilie; Le Hello, Simon; Michel, Valerie; Jourdan-Da Silva, Nathalie; Lailler, Renaud; Brisabois, Anne; Cadel-Six, Sabrina

2017-01-01

Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) figures among the most frequently isolated Salmonella strains in humans in France. This serovar may affect production and animal health mainly in cattle herds with corresponding high economic losses. Given that the current gold standard method, pulsed-field gel electrophoresis (PFGE), provides insufficient discrimination for epidemiological investigations, we propose a standard operating procedure in this study for multiple-locus variable number tandem repeat analysis (MLVA) of S. Dublin, suitable for inter-laboratory surveillance. An in silico analysis on the genome of S. Dublin strains CT_02021853 was performed to identify appropriate microsatellite regions. Of 21 VNTR loci screened, six were selected and 401 epidemiologically unrelated and related strains, isolated from humans, food and animals were analyzed to assess performance criteria such as typeability, discriminatory power and epidemiological concordance. The MLVA scheme developed was applied to an outbreak involving Saint-Nectaire cheese for which investigations were conducted in France in 2012, making it possible to discriminate between epidemiologically related strains and sporadic case strains, while PFGE assigned only a single profile. The six loci selected were sequenced on a large set of strains to determine the sequence of the repeated units and flanking regions, and their stability was evaluated in vivo through the analysis of the strains investigated from humans, food and the farm environment during the outbreak. The six VNTR selected were found to be stable and the discriminatory power of the MLVA method developed was calculated to be 0.954 compared with that for PFGE, which was only 0.625. Twenty-four reference strains were selected from the 401 examined strains in order to represent most of the allele diversity observed for each locus. This reference set can be used to harmonize MLVA results and allow data exchange between laboratories. This original MLVA protocol could be used easily and routinely for monitoring of serovar Dublin isolates and for conducting outbreak investigations. PMID:28289408

MLVA and MLST typing of Brucella from Qinghai, China.

PubMed

Ma, Jun-Ying; Wang, Hu; Zhang, Xue-Fei; Xu, Li-Qing; Hu, Gui-Ying; Jiang, Hai; Zhao, Fang; Zhao, Hong-Yan; Piao, Dong-Ri; Qin, Yu-Min; Cui, Bu-Yun; Lin, Gong-Hua

2016-04-13

The Qinghai-Tibet Plateau (QTP) of China is an extensive pastoral and semi-pastoral area, and because of poverty and bad hygiene conditions, Brucella is highly prevalent in this region. In order to adequately prevent this disease in the QTP region it is important to determine the identity of Brucella species that caused the infection. A total of 65 Brucella isolates were obtained from human, livestock and wild animals in Qinghai, a Chinese province in east of the QTP. Two molecular typing methods, MLVA (multi-locus variable-number tandem-repeat analysis) and MLST (multi locus sequence typing) were used to identify the species and genotypes of these isolates. Both MLVA and MLST typing methods classified the 65 isolates into three species, B. melitensis, B. abortus and B. suis, which included 60, 4 and 1 isolates respectively. The MLVA method uniquely detected 34 (Bm01 ~ Bm34), 3 (Ba01 ~ Ba03), and 1 (Bs01) MLVA-16 genotypes for B. melitensis, B. abortus and B. suis, respectively. However, none of these genotypes exactly matched any of the genotypes in the Brucella2012 MLVA database. The MLST method identified five known ST types: ST7 and ST8 (B. melitensis), ST2 and ST5 (B. abortus), and ST14 (B. suis). We also detected a strain with a mutant type (3-2-3-2-?-5-3-8-2) of ST8 (3-2-3-2-1-5-3-8-2). Extensive genotype-sharing events could be observed among isolates from different host species. There were at least three Brucella (B. melitensis, B. abortus and B. suis) species in Qinghai, of which B. melitensis was the predominant species in the area examined. The Brucella population in Qinghai was very different from other regions of the world, possibly owing to the unique geographical characteristics such as extremely high altitude in QTP. There were extensive genotype-sharing events between isolates obtained from humans and other animals. Yaks, sheep and blue sheep were important zoonotic reservoirs of brucellosis causing species found in humans.

Multi-locus variable-number tandem repeat analysis of Bordetella pertussis isolates circulating in Poland in the period 1959-2013.

PubMed

Mosiej, Ewa; Krysztopa-Grzybowska, Katarzyna; Polak, Maciej; Prygiel, Marta; Lutyńska, Anna

2017-06-01

Despite the long history of pertussis vaccination and high vaccination coverage in Poland and many other developed countries, pertussis incidence rates have increased substantially, making whooping cough one of the most prevalent vaccine-preventable diseases. Among the factors potentially involved in pertussis resurgence, the adaptation of the Bordetella pertussis population to country-specific vaccine-induced immunity through selection of non-vaccine-type strains still needs detailed studies. Multi-locus variable-number tandem repeat analysis (MLVA), also linked to MLST and PFGE profiling, was applied to trace the genetic changes in the B. pertussis population circulating in Poland in the period 1959-2013 versus country-specific vaccine strains. Generally, among 174 B. pertussis isolates, 31 MLVA types were detected, of which 11 were not described previously. The predominant MLVA types of recent isolates in Poland were different from those of the typical isolates circulating in other European countries. The MT27 type, currently predominant in Europe, was rarely seen and detected in only five isolates among all studied. The features of the vaccine strains used for production of the pertussis component of a national whole-cell diphtheria-tetanus-pertussis (DTP) vaccine, as studied by MLVA and MLST tools, were found to not match those observed in the currently circulating B. pertussis isolates in Poland. Differences traced by MLVA in relation to the MLST and PFGE profiling confirmed that the B. pertussis strain types currently observed elsewhere in Europe, even if appearing in Poland, were not able to successfully disseminate within a human population in Poland that has been vaccinated with a whole-cell pertussis vaccine not used in other countries.

Longitudinal study of Salmonella 1,4,[5],12:i:- shedding in five Australian pig herds.

PubMed

Weaver, T; Valcanis, M; Mercoulia, K; Sait, M; Tuke, J; Kiermeier, A; Hogg, G; Pointon, A; Hamilton, D; Billman-Jacobe, H

2017-01-01

The shedding patterns of Salmonella spp. and MLVA profiles of Salmonella enterica subspecies enterica (I) serotype 1,4,[5],12:i:- were monitored in a 12-month longitudinal observational study of five pig herds to inform management; provide indications of potential hazard load at slaughter; and assist evaluation of MLVA for use by animal and public health practitioners. Twenty pooled faecal samples, stratified by age group, were collected quarterly. When Salmonella was cultured, multiple colonies were characterized by serotyping and where S. Typhimurium-like serovars were confirmed, isolates were further characterized by phage typing and multiple locus variable number tandem repeat analysis (MLVA). Salmonella was detected in 43% of samples. Salmonella 1,4,[5],12:i- was one of several serovars that persisted within the herds and was found among colonies from each production stage. Virtually all Salmonella 1,4,[5],12:i:- isolates were phage type 193, but exhibited 12 different, closely-related MLVA profiles. Salmonella 1,4,[5],12:i:- diversity within herds was low and MLVA profiles were stable indicating colonization throughout the herds and suggesting each farm had an endemic strain. High prevalence of S. 1,4,[5],12:i:- specific shedding among terminal animals indicated high hazard load at slaughter, suggesting that primary production may be an important pathway of S. 1,4,[5],12:i:- into the human food chain, this has implications for on-farm management and the application and targeting control measures and further evidence of the need for effective process control procedures to be in place during slaughter and in pork boning rooms. These findings have implications for animal health and food safety risk mitigation and risk management. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

First molecular characterisation of a Brazilian Burkholderia mallei strain isolated from a mule in 2016.

PubMed

Laroucau, K; Lucia de Assis Santana, V; Girault, G; Martin, B; Miranda da Silveira, P P; Brasil Machado, M; Joseph, M; Wernery, R; Wernery, U; Zientara, S; Madani, N

2018-01-01

We present the first molecular characterisation based on MLVA and SNP analysis of a strain of Burkholderia mallei isolated from a mule found dead in Brazil in 2016. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial distribution of Legionella pneumophila MLVA-genotypes in a drinking water system.

PubMed

Rodríguez-Martínez, Sarah; Sharaby, Yehonatan; Pecellín, Marina; Brettar, Ingrid; Höfle, Manfred; Halpern, Malka

2015-06-15

Bacteria of the genus Legionella cause water-based infections, resulting in severe pneumonia. To improve our knowledge about Legionella spp. ecology, its prevalence and its relationships with environmental factors were studied. Seasonal samples were taken from both water and biofilm at seven sampling points of a small drinking water distribution system in Israel. Representative isolates were obtained from each sample and identified to the species level. Legionella pneumophila was further determined to the serotype and genotype level. High resolution genotyping of L. pneumophila isolates was achieved by Multiple-Locus Variable number of tandem repeat Analysis (MLVA). Within the studied water system, Legionella plate counts were higher in summer and highly variable even between adjacent sampling points. Legionella was present in six out of the seven selected sampling points, with counts ranging from 1.0 × 10(1) to 5.8 × 10(3) cfu/l. Water counts were significantly higher in points where Legionella was present in biofilms. The main fraction of the isolated Legionella was L. pneumophila serogroup 1. Serogroup 3 and Legionella sainthelensis were also isolated. Legionella counts were positively correlated with heterotrophic plate counts at 37 °C and negatively correlated with chlorine. Five MLVA-genotypes of L. pneumophila were identified at different buildings of the sampled area. The presence of a specific genotype, "MLVA-genotype 4", consistently co-occurred with high Legionella counts and seemed to "trigger" high Legionella counts in cold water. Our hypothesis is that both the presence of L. pneumophila in biofilm and the presence of specific genotypes, may indicate and/or even lead to high Legionella concentration in water. This observation deserves further studies in a broad range of drinking water systems to assess its potential for general use in drinking water monitoring and management. Copyright © 2015 Elsevier Ltd. All rights reserved.

Molecular strain typing of Brucella abortus isolates from Italy by two VNTR allele sizing technologies.

PubMed

De Santis, Riccardo; Ancora, Massimo; De Massis, Fabrizio; Ciammaruconi, Andrea; Zilli, Katiuscia; Di Giannatale, Elisabetta; Pittiglio, Valentina; Fillo, Silvia; Lista, Florigio

2013-10-01

Brucellosis, one of the most important re-emerging zoonoses in many countries, is caused by bacteria belonging to the genus Brucella. Furthermore these bacteria represent potential biological warfare agents and the identification of species and biovars of field strains may be crucial for tracing back source of infection, allowing to discriminate naturally occurring outbreaks instead of bioterrorist events. In the last years, multiple-locus variable-number tandem repeat analysis (MLVA) has been proposed as complement of the classical biotyping methods and it has been applied for genotyping large collections of Brucella spp. At present, the MLVA band profiles may be resolved by automated or manual procedures. The Lab on a chip technology represents a valid alternative to standard genotyping techniques (as agarose gel electrophoresis) and it has been previously used for Brucella genotyping. Recently, a new high-throughput genotyping analysis system based on capillary gel electrophoresis, the QIAxcel, has been described. The aim of the study was to evaluate the ability of two DNA sizing equipments, the QIAxcel System and the Lab chip GX, to correctly call alleles at the sixteen loci including one frequently used MLVA assay for Brucella genotyping. The results confirmed that these technologies represent a meaningful advancement in high-throughput Brucella genotyping. Considering the accuracy required to confidently resolve loci discrimination, QIAxcel shows a better ability to measure VNTR allele sizes compared to LabChip GX.

Molecular characterization of enterohemorrhagic Escherichia coli O157:H7 isolates dispersed across Japan by pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analysis.

PubMed

Pei, Yingxin; Terajima, Jun; Saito, Yasunori; Suzuki, Reiko; Takai, Nobuko; Izumiya, Hidemasa; Morita-Ishihara, Tomoko; Ohnishi, Makoto; Miura, Masashi; Iyoda, Sunao; Mitobe, Jiro; Wang, Binyou; Watanabe, Haruo

2008-01-01

We identified seven distinct subtypes of enterohemorrhagic Escherichia coli (EHEC) O157:H7 isolates that were derived from sporadic cases and outbreaks from multiple prefectures in Japan in 2005. A surveillance system utilizing pulsed-field gel electrophoresis (PFGE), PulseNet Japan, was used. Some strains showed indistinguishable PFGE patterns using another restriction enzyme (BlnI or SpeI) in each subtype of EHEC O157:H7 isolates that were routinely subtyped by the XbaI PFGE pattern. In order to examine the genotypic relatedness of these strains, we carried out a multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA). By using the MLVA system, we found that three of seven subtypes of EHEC O157:H7 strains that were isolated from sporadic cases dispersed across multiple prefectures within a few months showed indistinguishable PFGE patterns and identical MLVA types. Strains belonging to the other four subtypes of EHEC O157:H7 in the PFGE analysis were further classified into different clusters of EHEC O157:H7. Therefore, compared to PFGE, MLVA showed greater discriminatory power with respect to analysis of the isolates in this study.

Persistence of the same genetic type of Mycoplasma hyopneumoniae in a closed herd for at least two years.

PubMed

Rebaque, Florencia; Camacho, Pablo; Parada, Julián; Lucchesi, Paula; Ambrogi, Arnaldo; Tamiozzo, Pablo

2017-10-20

Two cross-sectional studies were carried out in 2013 and 2015 monitoring for Mycoplasma hyopneumoniae presence in a swine farm. In these studies, the genetic diversity of M. hyopneumoniae was assessed in clinical specimens using a Multiple Locus Variable-number tandem repeat Analysis (MLVA) targeting P97 R1, P146 R3 and H4 loci. The samples from August 2015 showed the MLVA profile prevalent in June 2013, therefore it can be concluded that a same genetic type of M. hyopneumoniae can persist for at least two years in a closed herd. In addition, the nested PCR reactions implemented in this study showed to be useful for MLVA typing in non-invasive clinical samples. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Molecular Epidemiology of Cholera Outbreaks during the Rainy Season in Mandalay, Myanmar.

PubMed

Roobthaisong, Amonrattana; Okada, Kazuhisa; Htun, Nilar; Aung, Wah Wah; Wongboot, Warawan; Kamjumphol, Watcharaporn; Han, Aye Aye; Yi, Yi; Hamada, Shigeyuki

2017-11-01

Cholera, caused by Vibrio cholerae , remains a global threat to public health. In Myanmar, the availability of published information on the occurrence of the disease is scarce. We report here that cholera incidence in Mandalay generally exhibited a single annual peak, with an annual average of 312 patients with severe dehydration over the past 5 years (since 2011) and was closely associated with the rainy season. We analyzed cholera outbreaks, characterized 67 isolates of V. cholerae serogroup O1 in 2015 from patients from Mandalay, and compared them with 22 V. cholerae O1 isolates (12 from Mandalay and 10 from Yangon) in 2014. The isolates carried the classical cholera toxin B subunit ( ctxB ), the toxin-coregulated pilus A ( tcpA ) of Haitian type, and repeat sequence transcriptional regulator ( rstR ) of El Tor type. Two molecular typing methods, pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analysis (MLVA), differentiated the 89 isolates into seven pulsotypes and 15 MLVA profiles. Pulsotype Y15 and one MLVA profile (11, 7, 7, 16, 7) were predominantly found in the isolates from cholera outbreaks in Mandalay, 2015. Pulsotypes Y11, Y12, and Y15 with some MLVA profiles were detected in the isolates from two remote areas, Mandalay and Yangon, with temporal changes. These data suggested that cholera spread from the seaside to the inland area in Myanmar.

Population and evolutionary dynamics of Shiga-toxin producing Escherichia coli O157 in a beef herd: A longitudinal study.

PubMed

Jones, Meghan; Octavia, Sophie; Lammers, Geraldine; Heller, Jane; Lan, Ruiting

2017-05-01

Shiga toxin producing Escherichia coli O157:H7 (STEC O157) is naturally found in the gastrointestinal tract of cattle and can cause severe disease in humans. There is limited understanding of the population dynamics and microevolution of STEC O157 at herd level. In this study, isolates from a closed beef herd of 23 cows were used to examine the population turnover in the herd. Of the nine STEC O157 clades previously described, clade 7 was found in 162 of the 169 isolates typed. Multiple locus variable number tandem repeat analysis (MLVA) differentiated 169 isolates into 33 unique MLVA types. Five predominant MLVA types were evident with most of the remaining types containing only a single isolate. MLVA data suggest that over time clonal replacement occurred within the herd. Genome sequencing of 18 selected isolates found that the isolates were divided into four lineages, representing four different 'clones' in the herd. Genome data confirmed clonal replacement over time and provided evidence of cross transmission of strains between cows. The findings enhanced our understanding of the population dynamics of STEC O157 in its natural host that will help developing effective control measures to prevent the spread of the pathogen to the human population. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Bacillus anthracis Diversity and Geographic Potential across Nigeria, Cameroon and Chad: Further Support of a Novel West African Lineage

PubMed Central

Blackburn, Jason K.; Odugbo, Moses Ode; Van Ert, Matthew; O’Shea, Bob; Mullins, Jocelyn; Perrenten, Vincent; Maho, Angaya; Hugh-Jones, Martin; Hadfield, Ted

2015-01-01

Zoonoses, diseases affecting both humans and animals, can exert tremendous pressures on human and veterinary health systems, particularly in resource limited countries. Anthrax is one such zoonosis of concern and is a disease requiring greater public health attention in Nigeria. Here we describe the genetic diversity of Bacillus anthracis in Nigeria and compare it to Chad, Cameroon and a broader global dataset based on the multiple locus variable number tandem repeat (MLVA-25) genetic typing system. Nigerian B. anthracis isolates had identical MLVA genotypes and could only be resolved by measuring highly mutable single nucleotide repeats (SNRs). The Nigerian MLVA genotype was identical or highly genetically similar to those in the neighboring countries, confirming the strains belong to this unique West African lineage. Interestingly, sequence data from a Nigerian isolate shares the anthrose deficient genotypes previously described for strains in this region, which may be associated with vaccine evasion. Strains in this study were isolated over six decades, indicating a high level of temporal strain stability regionally. Ecological niche models were used to predict the geographic distribution of the pathogen for all three countries. We describe a west-east habitat corridor through northern Nigeria extending into Chad and Cameroon. Ecological niche models and genetic results show B. anthracis to be ecologically established in Nigeria. These findings expand our understanding of the global B. anthracis population structure and can guide regional anthrax surveillance and control planning. PMID:26291625

A Case-Control Study of Molecular Epidemiology in Relation to Azithromycin Resistance in Neisseria gonorrhoeae Isolates Collected in Amsterdam, the Netherlands, between 2008 and 2015

PubMed Central

Wind, Carolien M.; Bruisten, Sylvia M.; Schim van der Loeff, Maarten F.; Dierdorp, Mirjam; de Vries, Henry J. C.

2017-01-01

ABSTRACT Neisseria gonorrhoeae resistance to ceftriaxone and azithromycin is increasing, which threatens the recommended dual therapy. We used molecular epidemiology to identify N. gonorrhoeae clusters and associations with azithromycin resistance in Amsterdam, the Netherlands. N. gonorrhoeae isolates (n = 143) were selected from patients visiting the Amsterdam STI Outpatient Clinic from January 2008 through September 2015. We included all 69 azithromycin-resistant isolates (MIC ≥ 2.0 mg/liter) and 74 frequency-matched susceptible controls (MIC ≤ 0.25 mg/liter). The methods used were 23S rRNA and mtrR sequencing, N. gonorrhoeae multiantigen sequence typing (NG-MAST), N. gonorrhoeae multilocus variable-number tandem-repeat analysis (NG-MLVA), and a specific PCR to detect mosaic penA genes. A hierarchical cluster analysis of NG-MLVA related to resistance and epidemiological characteristics was performed. Azithromycin-resistant isolates had C2611T mutations in 23S rRNA (n = 62, 89.9%, P < 0.001) and were NG-MAST genogroup G2992 (P < 0.001), G5108 (P < 0.001), or G359 (P = 0.02) significantly more often than susceptible isolates and were more often part of NG-MLVA clusters (P < 0.001). Two resistant isolates (2.9%) had A2059G mutations, and five (7.3%) had wild-type 23S rRNA. No association between mtrR mutations and azithromycin resistance was found. Twenty-four isolates, including 10 azithromycin-resistant isolates, showed reduced susceptibility to extended-spectrum cephalosporins. Of these, five contained a penA mosaic gene. Four of the five NG-MLVA clusters contained resistant and susceptible isolates. Two clusters consisting mainly of resistant isolates included strains from men who have sex with men and from heterosexual males and females. The co-occurrence of resistant and susceptible strains in NG-MLVA clusters and the frequent occurrence of resistant strains outside of clusters suggest that azithromycin resistance develops independently from the background genome. PMID:28373191

Diversification and Distribution of Ruminant Chlamydia abortus Clones Assessed by MLST and MLVA.

PubMed

Siarkou, Victoria I; Vorimore, Fabien; Vicari, Nadia; Magnino, Simone; Rodolakis, Annie; Pannekoek, Yvonne; Sachse, Konrad; Longbottom, David; Laroucau, Karine

2015-01-01

Chlamydia abortus, an obligate intracellular bacterium, is the most common infectious cause of abortion in small ruminants worldwide and has zoonotic potential. We applied multilocus sequence typing (MLST) together with multiple-locus variable-number tandem repeat analysis (MLVA) to genotype 94 ruminant C. abortus strains, field isolates and samples collected from 1950 to 2011 in diverse geographic locations, with the aim of delineating C. abortus lineages and clones. MLST revealed the previously identified sequence types (STs) ST19, ST25, ST29 and ST30, plus ST86, a recently-assigned type on the Chlamydiales MLST website and ST87, a novel type harbouring the hemN_21 allele, whereas MLVA recognized seven types (MT1 to MT7). Minimum-spanning-tree analysis suggested that all STs but one (ST30) belonged to a single clonal complex, possibly reflecting the short evolutionary timescale over which the predicted ancestor (ST19) has diversified into three single-locus variants (ST86, ST87 and ST29) and further, through ST86 diversification, into one double-locus variant (ST25). ST descendants have probably arisen through a point mutation evolution mode. Interestingly, MLVA showed that in the ST19 population there was a greater genetic diversity than in other STs, most of which exhibited the same MT over time and geographical distribution. However, the evolutionary pathways of C. abortus STs seem to be diverse across geographic distances with individual STs restricted to particular geographic locations. The ST30 singleton clone displaying geographic specificity and represented by the Greek strains LLG and POS was effectively distinguished from the clonal complex lineage, supporting the notion that possibly two separate host adaptations and hence independent bottlenecks of C. abortus have occurred through time. The combination of MLST and MLVA assays provides an additional level of C. abortus discrimination and may prove useful for the investigation and surveillance of emergent C. abortus clonal populations.

Genotypic characterization of gentamicin and cephalosporin resistant Escherichia coli isolates from blood cultures in a Norwegian university hospital 2011-2015.

PubMed

Fladberg, Øyvind Andreas; Jørgensen, Silje Bakken; Aamot, Hege Vangstein

2017-01-01

Cephalosporin resistance in clinical E. coli isolates is increasing internationally. The increase has been caused by virulent and often multidrug-resistant clones, especially the extended spectrum β-lactamase (ESBL) producing E. coli clone O25b-ST131. In Norway, recommended empirical treatment of sepsis consists of gentamicin and penicillin combined, or a broad-spectrum cephalosporin. To investigate if increased gentamicin and cephalosporins resistance rates in our hospital could be caused by specific clones, we conducted a retrospective study on E. coli blood culture isolates from 2011 through 2015. All E. coli isolates non-susceptible to gentamicin and/or third-generation cephalosporins were genotyped using multiple-locus variable-number of tandem repeat analysis (MLVA) and compared with antibiotic susceptible isolates. The frequency of the most common genes causing ESBL production ( bla CTX-M , bla ampC ) was examined by Real-Time PCR. A total of 158 cephalosporin and/or gentamicin resistant and 97 control isolates were differentiated into 126 unique MLVA types. Of these, 31% of the isolates belonged to a major MLVA cluster consisting of 41% of the gentamicin resistant and 35% of the cephalosporin resistant isolates. The majority (65/80 isolates) of this MLVA cluster contained MLVA types associated with the E. coli O25b-ST131 clone. Genes encoding CTX-M enzyme phylogroups 1 and 9 occurred in 65% and 19% of cephalosporin resistant isolates, respectively, whereas bla ampC-CIT was identified in 3%. No local E. coli bacteraemia clone was identified. Antibiotic resistance was dispersed over a variety of genotypes. However, association with the international E. coli O25b-ST131 clone was frequent and may be an important driver behind increased resistance rates. Monitoring and preventing dissemination of these resistant clones are important for continued optimal treatment.

Highly diverse MLVA-ompA genotypes of rectal Chlamydia trachomatis among men who have sex with men in Brighton, UK and evidence for an HIV-related sexual network.

PubMed

Labiran, Clare; Marsh, Peter; Zhou, Judith; Bannister, Alan; Clarke, Ian Nicholas; Goubet, Stephanie; Soni, Suneeta

2016-06-01

In this prospective study, we aimed to determine the distribution of genotypes by multilocus variable number tandem repeat (VNTR) analysis plus analysis of the ompA gene (MLVA-ompA) of rectal Chlamydia trachomatis among men who have sex with men (MSM) attending Brighton Genitourinary Medicine (GUM) Clinic and to examine any correlations with clinical variables, including HIV status, and to isolate rectal C. trachomatis cultures maximising the possibility of obtaining complete genotyping data. Samples were assigned genotypes by PCR and sequencing of the markers of the MLVA-ompA genotyping system. Rectal C. trachomatis was isolated in cell culture using McCoy cells. Data regarding demographics, HIV status, rectal symptoms and history of sexually transmitted infections, including C. trachomatis, were collected. 1809 MSM attending the clinic between October 2011 and January 2013 took part in the study, 112 (6.2%) of whom had rectal samples that tested positive for C. trachomatis. 85/112 (75.9%) C. trachomatis-positive rectal samples were assigned 66 different genotypes. Two distinct genotype subclusters were identified: subcluster 1 consisted of more HIV-negative men than subcluster 2 (p=0.025), and the MLVA-ompA genotypes in these subclusters reflected this. Isolates were successfully cultured from 37 of the 112 specimens, from which 27 otherwise unobtainable (from direct PCR) MLVA-ompA genotypes were gained. The most prevalent genotypes were G, E and D representing some overlap with the heterosexual distribution in UK. Subcluster 1 consisted of more 'heterosexual genotypes' and significantly more HIV-negative men than subcluster 2, associated with 'MSM genotypes'. There was a higher diversity of C. trachomatis strains among MSM in Brighton than observed in other cities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Rapid and reliable discrimination between Shigella species and Escherichia coli using MALDI-TOF mass spectrometry.

PubMed

Paauw, Armand; Jonker, Debby; Roeselers, Guus; Heng, Jonathan M E; Mars-Groenendijk, Roos H; Trip, Hein; Molhoek, E Margo; Jansen, Hugo-Jan; van der Plas, Jan; de Jong, Ad L; Majchrzykiewicz-Koehorst, Joanna A; Speksnijder, Arjen G C L

2015-01-01

E. coli-Shigella species are a cryptic group of bacteria in which the Shigella species are distributed within the phylogenetic tree of E. coli. The nomenclature is historically based and the discrimination of these genera developed as a result of the epidemiological need to identify the cause of shigellosis, a severe disease caused by Shigella species. For these reasons, this incorrect classification of shigellae persists to date, and the ability to rapidly characterize E. coli and Shigella species remains highly desirable. Until recently, existing matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) assays used to identify bacteria could not discriminate between E. coli and Shigella species. Here we present a rapid classification method for the E. coli-Shigella phylogroup based on MALDI-TOF MS which is supported by genetic analysis. E. coli and Shigella isolates were collected and genetically characterized by MLVA. A custom reference library for MALDI-TOF MS that represents the genetic diversity of E. coli and Shigella strains was developed. Characterization of E. coli and Shigella species is based on an approach with Biotyper software. Using this reference library it was possible to distinguish between Shigella species and E. coli. Of the 180 isolates tested, 94.4% were correctly classified as E. coli or shigellae. The results of four (2.2%) isolates could not be interpreted and six (3.3%) isolates were classified incorrectly. The custom library extends the existing MALDI-TOF MS method for species determination by enabling rapid and accurate discrimination between Shigella species and E. coli. Copyright © 2015 Elsevier GmbH. All rights reserved.

Genotyping of Coxiella burnetii from domestic ruminants and human in Hungary: indication of various genotypes.

PubMed

Sulyok, Kinga M; Kreizinger, Zsuzsa; Hornstra, Heidie M; Pearson, Talima; Szigeti, Alexandra; Dán, Ádám; Balla, Eszter; Keim, Paul S; Gyuranecz, Miklós

2014-05-07

Information about the genotypic characteristic of Coxiella burnetii from Hungary is lacking. The aim of this study is to describe the genetic diversity of C. burnetii in Hungary and compare genotypes with those found elsewhere. A total of 12 samples: (cattle, n = 6, sheep, n = 5 and human, n = 1) collected from across Hungary were studied by a 10-loci multispacer sequence typing (MST) and 6-loci multiple-locus variable-number of tandem repeat analysis (MLVA). Phylogenetic relationships among MST genotypes show how these Hungarian samples are related to others collected around the world. Three MST genotypes were identified: sequence type (ST) 20 has also been identified in ruminants from other European countries and the USA, ST28 was previously identified in Kazakhstan, and the proposed ST37 is novel. All MST genotypes yielded different MLVA genotypes and three different MLVA genotypes were identified within ST20 samples alone. Two novel MLVA types 0-9-5-5-6-2 (AG) and 0-8-4-5-6-2 (AF) (Ms23-Ms24-Ms27-Ms28-Ms33-Ms34) were defined in the ovine materials correlated with ST28 and ST37. Samples from different parts of the phylogenetic tree were associated with different hosts, suggesting host-specific adaptations. Even with the limited number of samples analysed, this study revealed high genetic diversity among C. burnetii in Hungary. Understanding the background genetic diversity will be essential in identifying and controlling outbreaks.

New Multilocus Variable-Number Tandem-Repeat Analysis Tool for Surveillance and Local Epidemiology of Bacterial Leaf Blight and Bacterial Leaf Streak of Rice Caused by Xanthomonas oryzae

PubMed Central

Poulin, L.; Grygiel, P.; Magne, M.; Rodriguez-R, L. M.; Forero Serna, N.; Zhao, S.; El Rafii, M.; Dao, S.; Tekete, C.; Wonni, I.; Koita, O.; Pruvost, O.; Verdier, V.; Vernière, C.

2014-01-01

Multilocus variable-number tandem-repeat analysis (MLVA) is efficient for routine typing and for investigating the genetic structures of natural microbial populations. Two distinct pathovars of Xanthomonas oryzae can cause significant crop losses in tropical and temperate rice-growing countries. Bacterial leaf streak is caused by X. oryzae pv. oryzicola, and bacterial leaf blight is caused by X. oryzae pv. oryzae. For the latter, two genetic lineages have been described in the literature. We developed a universal MLVA typing tool both for the identification of the three X. oryzae genetic lineages and for epidemiological analyses. Sixteen candidate variable-number tandem-repeat (VNTR) loci were selected according to their presence and polymorphism in 10 draft or complete genome sequences of the three X. oryzae lineages and by VNTR sequencing of a subset of loci of interest in 20 strains per lineage. The MLVA-16 scheme was then applied to 338 strains of X. oryzae representing different pathovars and geographical locations. Linkage disequilibrium between MLVA loci was calculated by index association on different scales, and the 16 loci showed linear Mantel correlation with MLSA data on 56 X. oryzae strains, suggesting that they provide a good phylogenetic signal. Furthermore, analyses of sets of strains for different lineages indicated the possibility of using the scheme for deeper epidemiological investigation on small spatial scales. PMID:25398857

Multiple-Locus Variable-Number Tandem-Repeat Analysis in Genotyping Yersinia enterocolitica Strains from Human and Porcine Origins

PubMed Central

Laukkanen-Ninios, R.; Ortiz Martínez, P.; Siitonen, A.; Fredriksson-Ahomaa, M.; Korkeala, H.

2013-01-01

Sporadic and epidemiologically linked Yersinia enterocolitica strains (n = 379) isolated from fecal samples from human patients, tonsil or fecal samples from pigs collected at slaughterhouses, and pork samples collected at meat stores were genotyped using multiple-locus variable-number tandem-repeat analysis (MLVA) with six loci, i.e., V2A, V4, V5, V6, V7, and V9. In total, 312 different MLVA types were found. Similar types were detected (i) in fecal samples collected from human patients over 2 to 3 consecutive years, (ii) in samples from humans and pigs, and (iii) in samples from pigs that originated from the same farms. Among porcine strains, we found farm-specific MLVA profiles. Variations in the numbers of tandem repeats from one to four for variable-number tandem-repeat (VNTR) loci V2A, V5, V6, and V7 were observed within a farm. MLVA was applicable for serotypes O:3, O:5,27, and O:9 and appeared to be a highly discriminating tool for distinguishing sporadic and outbreak-related strains. With long-term use, interpretation of the results became more challenging due to variations in more-discriminating loci, as was observed for strains originating from pig farms. Additionally, we encountered unexpectedly short V2A VNTR fragments and sequenced them. According to the sequencing results, updated guidelines for interpreting V2A VNTR results were prepared. PMID:23637293

Highly diverse variable number tandem repeat loci in the E. coli O157:H7 and O55:H7 genomes for high-resolution molecular typing.

PubMed

Keys, C; Kemper, S; Keim, P

2005-01-01

Evaluation of the Escherichia coli genome for variable number tandem repeat (VNTR) loci in order to provide a subtyping tool with greater discrimination and more efficient capacity. Twenty-nine putative VNTR loci were identified from the E. coli genomic sequence. Their variability was validated by characterizing the number of repeats at each locus in a set of 56 E. coli O157:H7/HN and O55:H7 isolates. An optimized multiplex assay system was developed to facility high capacity analysis. Locus diversity values ranged from 0.23 to 0.95 while the number of alleles ranged from two to 29. This multiple-locus VNTR analysis (MLVA) data was used to describe genetic relationships among these isolates and was compared with PFGE (pulse field gel electrophoresis) data from a subset of the same strains. Genetic similarity values were highly correlated between the two approaches, through MLVA was capable of discrimination amongst closely related isolates when PFGE similar values were equal to 1.0. Highly variable VNTR loci exist in the E. coli O157:H7 genome and are excellent estimators of genetic relationships, in particular for closely related isolates. Escherichia coli O157:H7 MLVA offers a complimentary analysis to the more traditional PFGE approach. Application of MLVA to an outbreak cluster could generate superior molecular epidemiology and result in a more effective public health response.

[Molecular typing characterization of food-borne methicillin-resistant Staphylococcus aureus in China].

PubMed

Bai, Y; Wang, W; Yan, L; Yang, S R; Yan, S F; Dong, Y P; Zhao, B C; Zhao, Y Y; Xu, J; Hu, Y J; Li, F Q

2018-04-06

Objective: To analyses the antimicrobial resistance and molecular characterization of 21 MRSA isolates cultured from retail foods from different provinces in China, and evaluate the molecular typing methods. Methods: Twenty-one MRSA isolates were obtained from national foodborne pathogen surveillance network in 2012 (Chinese salad, n= 3; milk, n= 1; cake, n= 2; rice, n= 1; cold noodle, n= 1; spiced beef, n= 1; dumpling, n= 1; packed meal, n= 1; salad, n= 1; raw pork, n= 9). The antimicrobial resistance of 21 strains to 12 antimicrobial agents was tested by broth dilution method. Polymerase chain reaction (PCR) and DNA sequencing were performed to obtain the genetic types of MLST (ST) and spa typing. The clonal complex (CC) was assigned by eBURST soft and the MLVA type (MT) and MLVA complex (MC) were identified via the database of the MLVA website (http://www.mlva.net). Sma I pulsed-field gel electrophoresis ( Sma Ⅰ-PFGE) was also carried out to obtain the PFGE patterns of 21 strains. The genetic diversity and discriminatory power of typing were calculated by the Simpson's index of diversity (diversity index, DI) to find out the best genotyping method for MRSA. Results: All MRSA isolates showed multi-drug resistance(MDR), and were resistant to oxacillin, benzylpenicillin, clindamycin and erythromycin, and 71.4% (15/21), 47.6% (10/21), 42.9% (9/21) and 28.6% (6/21) of the MRSA isolates were resistant to tetracycline, ciprofloxacin, trimethoprim/sulfamethoxazole and gentamicin, respectively. Moreover, one strain was found to be resistant to all three antimicrobials of levofloxacin, moxifloxacin and rifampicin. Great diversity was found in these food-associated MRSA (6 STs, 7 spa types, and 9 MTs). PFGE patterns were more diverse than those of other three molecular typing methods (19 pulse types). The index of diversity (DI) of PFGE, MLVA, spa typing and MLST was 0.99, 0.80, 0.73, and 0.61, respectively. Among the MRSA isolates, CC9-ST9-t899-MT929-MC2236 (PFGE Cluster Ⅴ) was the most prevalent clone, which were all cultured from raw pork (9 isolates). Besides, two MRSA were identified as CC59-ST338-t437-MT621-MC621 (PFGE Cluster Ⅳ). Different clone had their own resistance spectrum profiles. Conclusion: The food-borne MRSA isolates were all MDR in this study. Different clones had their own resistance spectrum profiles. MLVA represented a promising tool for molecular epidemiology tracing of MRSA in foodborne disease events.

High-throughput typing method to identify a non-outbreak-involved Legionella pneumophila strain colonizing the entire water supply system in the town of Rennes, France.

PubMed

Sobral, D; Le Cann, P; Gerard, A; Jarraud, S; Lebeau, B; Loisy-Hamon, F; Vergnaud, G; Pourcel, C

2011-10-01

Two legionellosis outbreaks occurred in the city of Rennes, France, during the past decade, requiring in-depth monitoring of Legionella pneumophila in the water network and the cooling towers in the city. In order to characterize the resulting large collection of isolates, an automated low-cost typing method was developed. The multiplex capillary-based variable-number tandem repeat (VNTR) (multiple-locus VNTR analysis [MLVA]) assay requiring only one PCR amplification per isolate ensures a high level of discrimination and reduces hands-on and time requirements. In less than 2 days and using one 4-capillary apparatus, 217 environmental isolates collected between 2000 and 2009 and 5 clinical isolates obtained during outbreaks in 2000 and 2006 in Rennes were analyzed, and 15 different genotypes were identified. A large cluster of isolates with closely related genotypes and representing 77% of the population was composed exclusively of environmental isolates extracted from hot water supply systems. It was not responsible for the known Rennes epidemic cases, although strains showing a similar MLVA profile have regularly been involved in European outbreaks. The clinical isolates in Rennes had the same genotype as isolates contaminating a mall's cooling tower. This study further demonstrates that unknown environmental or genetic factors contribute to the pathogenicity of some strains. This work illustrates the potential of the high-throughput MLVA typing method to investigate the origin of legionellosis cases by allowing the systematic typing of any new isolate and inclusion of data in shared databases.

Insights to Genetic Characterization Tools for Epidemiological Tracking of Francisella tularensis in Sweden

PubMed Central

Wahab, Tara; Birdsell, Dawn N.; Hjertqvist, Marika; Mitchell, Cedar L.; Wagner, David M.; Keim, Paul S.; Hedenström, Ingela; Löfdahl, Sven

2014-01-01

Tularaemia, caused by the bacterium Francisella tularensis, is endemic in Sweden and is poorly understood. The aim of this study was to evaluate the effectiveness of three different genetic typing systems to link a genetic type to the source and place of tularemia infection in Sweden. Canonical single nucleotide polymorphisms (canSNPs), MLVA including five variable number of tandem repeat loci and PmeI-PFGE were tested on 127 F. tularensis positive specimens collected from Swedish case-patients. All three typing methods identified two major genetic groups with near-perfect agreement. Higher genetic resolution was obtained with canSNP and MLVA compared to PFGE; F. tularensis samples were first assigned into ten phylogroups based on canSNPs followed by 33 unique MLVA types. Phylogroups were geographically analysed to reveal complex phylogeographic patterns in Sweden. The extensive phylogenetic diversity found within individual counties posed a challenge to linking specific genetic types with specific geographic locations. Despite this, a single phylogroup (B.22), defined by a SNP marker specific to a lone Swedish sequenced strain, did link genetic type with a likely geographic place. This result suggests that SNP markers, highly specific to a particular reference genome, may be found most frequently among samples recovered from the same location where the reference genome originated. This insight compels us to consider whole-genome sequencing (WGS) as the appropriate tool for effectively linking specific genetic type to geography. Comparing the WGS of an unknown sample to WGS databases of archived Swedish strains maximizes the likelihood of revealing those rare geographically informative SNPs. PMID:25401326

Phenotypic and genetic characterization of Vibrio cholerae O1 clinical isolates collected through national antimicrobial resistance surveillance network in Nepal.

PubMed

Shakya, Geeta; Kim, Dong Wook; Clemens, John D; Malla, Sarala; Upadhyaya, Bishnu Prasad; Dumre, Shyam Prakash; Shrestha, Sirjana Devi; Adhikari, Shailaja; Sharma, Supriya; Rijal, Nisha; Shrestha, Sanjaya K; Mason, Carl; Kansakar, Palpasa

2012-08-01

Cholera occurs in sporadic cases and outbreaks in Nepal each year. Vibrio cholerae O1 (n = 522) isolated during 2007-2010 from diarrheal patients at 10 different hospital laboratories in Nepal were characterized. Biochemical and serologic identifications showed that all the isolates belonged to serogroup O1, El Tor biotype. Except 72 isolates of Inaba serotype isolated in the year 2007, all the remaining isolates were of Ogawa serotype. All isolates were resistant to nalidixic acid and furazolidone. Resistance to tetracycline, ciprofloxacin, erythromycin and co-trimoxazole were 21, 4, 16 and 90 % respectively. Seventy-seven of these isolates were selected for further characterization for ctxB gene and MLVA typing. Two different variants of classical type cholera toxin were observed. Ogawa strains from 2007 and 2010-Western Nepal outbreak harbored CTX-3 type cholera toxin, whereas Inaba serotypes in 2007 and the remaining Ogawa serotypes in 2008-2010 harbored CTX 3b-type toxin. MLVA analysis showed circulation of four different groups of altered V. cholerae O1 El Tor strains. Two different profiles were seen among 2007 Inaba (9, 3, 6, x, x) and Ogawa (10, 7, 6, x, x) isolates. The MLVA profile of 2008 and 2009 Ogawa isolates were similar to those of Inaba strains of 2007. Isolates from 2010 also showed three different MLVA profiles; profile 9, 3, 6, x, x in 3 isolates, 11, 7, 6, x, x among 2010 Western Nepal outbreak strains and profile 8, 3, 6, x, x among isolates from Butwal and Kathmandu.

Use of multiple-locus variable-number tandem repeat analysis to evaluate Escherichia coli O157 subtype distribution and transmission dynamics following natural exposure on a closed beef feedlot facility.

PubMed

Williams, Michele L; Pearl, David L; Bishop, Katherine E; Lejeune, Jeffrey T

2013-10-01

To better understand the epizootiology of Escherichia coli O157:H7 among cattle, all E. coli O157 isolates recovered on a research feedlot during a single feeding period were characterized by multiple-locus variable-number tandem repeat analysis (MLVA). Three distinct MLVA subtypes (A, B, C), accounting for 24%, 15%, and 64% of total isolates, respectively, were identified. Subtypes A and B were isolated at the initiation of sampling, but their prevalence waned and subtype C, first isolated on the third sampling date, became the predominant subtype on the feedlot. Supershedding events, however, occurred with equal frequency for all three MLVA-types. Using a multilevel logistic regression model, we investigated whether the odds of shedding subtype C relative to subtypes A or B were associated with time, diet, or the presence of a penmate shedding high numbers of subtype C. Only time and exposure to an animal shedding MLVA-type C at 10³ colony-forming units or greater in the pen at the time of sampling were significantly associated with increased shedding of subtype C. High-level shedding of those E. coli O157 subtypes better suited for survival in the environment and/or in the host appear to play a significant role in the development of predominant E. coli O157 subtypes. Supershedding events alone are neither required nor sufficient to drive the epidemiology of specific E. coli O157 subtypes. Additional factors are necessary to direct successful on-farm transmission of E. coli O157.

Evaluation of a highly discriminating multiplex multi-locus variable-number of tandem-repeats (MLVA) analysis for Vibrio cholerae.

PubMed

Olsen, Jaran S; Aarskaug, Tone; Skogan, Gunnar; Fykse, Else Marie; Ellingsen, Anette Bauer; Blatny, Janet M

2009-09-01

Vibrio cholerae is the etiological agent of cholera and may be used in bioterror actions due to the easiness of its dissemination, and the public fear for acquiring the cholera disease. A simple and highly discriminating method for connecting clinical and environmental isolates of V. cholerae is needed in microbial forensics. Twelve different loci containing variable numbers of tandem-repeats (VNTRs) were evaluated in which six loci were polymorphic. Two multiplex reactions containing PCR primers targeting these six VNTRs resulted in successful DNA amplification of 142 various environmental and clinical V. cholerae isolates. The genetic distribution inside the V. cholerae strain collection was used to evaluate the discriminating power (Simpsons Diversity Index=0.99) of this new MLVA analysis, showing that the assay have a potential to differentiate between various strains, but also to identify those isolates which are collected from a common V. cholerae outbreak. This work has established a rapid and highly discriminating MLVA assay useful for track back analyses and/or forensic studies of V. cholerae infections.

Whole genome sequencing of Brucella melitensis isolated from 57 patients in Germany reveals high diversity in strains from Middle East.

PubMed

Georgi, Enrico; Walter, Mathias C; Pfalzgraf, Marie-Theres; Northoff, Bernd H; Holdt, Lesca M; Scholz, Holger C; Zoeller, Lothar; Zange, Sabine; Antwerpen, Markus H

2017-01-01

Brucellosis, a worldwide common bacterial zoonotic disease, has become quite rare in Northern and Western Europe. However, since 2014 a significant increase of imported infections caused by Brucella (B.) melitensis has been noticed in Germany. Patients predominantly originated from Middle East including Turkey and Syria. These circumstances afforded an opportunity to gain insights into the population structure of Brucella strains. Brucella-isolates from 57 patients were recovered between January 2014 and June 2016 with culture confirmed brucellosis by the National Consultant Laboratory for Brucella. Their whole genome sequences were generated using the Illumina MiSeq platform. A whole genome-based SNP typing assay was developed in order to resolve geographically attributed genetic clusters. Results were compared to MLVA typing results, the current gold-standard of Brucella typing. In addition, sequences were examined for possible genetic variation within target regions of molecular diagnostic assays. Phylogenetic analyses revealed spatial clustering and distinguished strains from different patients in either case, whereas multiple isolates from a single patient or technical replicates showed identical SNP and MLVA profiles. By including WGS data from the NCBI database, five major genotypes were identified. Notably, strains originating from Turkey showed a high diversity and grouped into seven subclusters of genotype II. MLVA analysis congruently clustered all isolates and predominantly matched the East Mediterranean genetic clade. This study confirms whole-genome based SNP-analysis as a powerful tool for accurate typing of B. melitensis. Furthermore it allows special allocation and therefore provides useful information on the geographic origin for trace-back analysis. However, the lack of reliable metadata in public databases often prevents a resolution below geographic regions or country levels and corresponding precise trace-back analysis. Once this obstacle is resolved, WGS-derived bacterial typing adds an important method to complement epidemiological surveys during outbreak investigations. This is the first report of a detailed genetic investigation of an extensive collection of B. melitensis strains isolated from human cases in Germany.

Isolation and molecular characterization of Salmonella enterica serovar Enteritidis from poultry house and clinical samples during 2010.

PubMed

Mezal, Ezat H; Sabol, Ashley; Khan, Mariam A; Ali, Nawab; Stefanova, Rossina; Khan, Ashraf A

2014-04-01

A total of 60 Salmonella enterica serovar (ser.) Enteritidis isolates, 28 from poultry houses and 32 from clinical samples, were isolated during 2010. These isolates were subjected to testing and analyzed for antibiotic resistance, virulence genes, plasmids and plasmid replicon types. To assess genetic diversity, pulsed-field gel electrophoresis (PFGE) fingerprinting, using the XbaI restriction enzyme, Multiple-Locus Variable-Number Tandem Repeat Analysis (MLVA) and plasmid profiles were performed. All isolates from poultry, and 10 out of 32 clinical isolates were sensitive to ampicillin, chloramphenicol, gentamicin, kanamycin, nalidixic acid, sulfisoxazole, streptomycin, and tetracycline. Twenty-one of thirty-two clinical isolates were resistant to ampicillin and tetracycline, and one isolate was resistant to nalidixic acid. PFGE typing of sixty ser. Enteritidis isolates by XbaI resulted in 10-12 bands and grouped into six clusters each with similarity from 95% to 81%. The MLVA analysis of sixty isolates gave 18 allele profiles with the majority of isolates displayed in three groups, and two clinical isolates found to be new in the PulseNet national MLVA database. All isolates were positive for 12 or more of the 17 virulence genes mostly found in S. enterica (spvB, spiA, pagC, msgA, invA, sipB, prgH, spaN, orgA, tolC, iroN, sitC, IpfC, sifA, sopB, and pefA) and negative for one gene (cdtB). All isolates carried a typical 58 kb plasmid, type Inc/FIIA. Three poultry isolates and one clinical isolate carried small plasmids with 3.8, 6, 7.6 and 11.5 kb. Ten of the clinical isolates carried plasmids, with sizes 36 and 38 kb, types IncL/M and IncN, and one isolate carried an 81 kb plasmid, type IncI. Southern hybridization of a plasmid with an Inc/FIIA gene probe hybridized one large 58 kb plasmid in all isolates. Several large and small plasmids from poultry isolates were not typed by our PCR-based method. These results confirmed that PFGE fingerprinting has limited discriminatory power for ser. Enteritidis in both poultry and clinical sources. However, the plasmid and MLVA allele profiles were a useful and important epidemiology tool to discriminate outbreak strains of ser. Enteritidis from poultry and clinical samples. Published by Elsevier Ltd.

Multistate Outbreak of Escherichia coli O157:H7 Infections Associated with Consumption of Fresh Spinach: United States, 2006.

PubMed

Sharapov, Umid M; Wendel, Arthur M; Davis, Jeffrey P; Keene, William E; Farrar, Jeffrey; Sodha, Samir; Hyytia-Trees, Eija; Leeper, Molly; Gerner-Smidt, Peter; Griffin, Patricia M; Braden, Chris

2016-12-01

During September to October, 2006, state and local health departments and the Centers for Disease Control and Prevention investigated a large, multistate outbreak of Escherichia coli O157:H7 infections. Case patients were interviewed regarding specific foods consumed and other possible exposures. E. coli O157:H7 strains isolated from human and food specimens were subtyped using pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analyses (MLVA). Two hundred twenty-five cases (191 confirmed and 34 probable) were identified in 27 states; 116 (56%) case patients were hospitalized, 39 (19%) developed hemolytic uremic syndrome, and 5 (2%) died. Among 176 case patients from whom E. coli O157:H7 with the outbreak genotype (MLVA outbreak strain) was isolated and who provided details regarding spinach exposure, 161 (91%) reported fresh spinach consumption during the 10 days before illness began. Among 116 patients who provided spinach brand information, 106 (91%) consumed bagged brand A. E. coli O157:H7 strains were isolated from 13 bags of brand A spinach collected from patients' homes; isolates from 12 bags had the same MLVA pattern. Comprehensive epidemiologic and laboratory investigations associated this large multistate outbreak of E. coli O157:H7 infections with consumption of fresh bagged spinach. MLVA, as a supplement to pulsed-field gel electrophoresis genotyping of case patient isolates, was important to discern outbreak-related cases. This outbreak resulted in enhanced federal and industry guidance to improve the safety of leafy green vegetables and launched an independent collaborative approach to produce safety research in 2007.

Diversity of Clostridium perfringens isolates from various sources and prevalence of conjugative plasmids.

PubMed

Park, Miseon; Deck, Joanna; Foley, Steven L; Nayak, Rajesh; Songer, J Glenn; Seibel, Janice R; Khan, Saeed A; Rooney, Alejandro P; Hecht, David W; Rafii, Fatemeh

2016-04-01

Clostridium perfringens is an important pathogen, causing food poisoning and other mild to severe infections in humans and animals. Some strains of C. perfringens contain conjugative plasmids, which may carry antimicrobial resistance and toxin genes. We studied genomic and plasmid diversity of 145 C. perfringens type A strains isolated from soils, foods, chickens, clinical samples, and domestic animals (porcine, bovine and canine), from different geographic areas in the United States between 1994 and 2006, using multiple-locus variable-number tandem repeat analysis (MLVA) and/or pulsed-field gel electrophoresis (PFGE). MLVA detected the genetic diversity in a majority of the isolates. PFGE, using SmaI and KspI, confirmed the MLVA results but also detected differences among the strains that could not be differentiated by MLVA. All of the PFGE profiles of the strains were different, except for a few of the epidemiologically related strains, which were identical. The PFGE profiles of strains isolated from the same domestic animal species were clustered more closely with each other than with other strains. However, a variety of C. perfringens strains with distinct genetic backgrounds were found among the clinical isolates. Variation was also observed in the size and number of plasmids in the strains. Primers for the internal fragment of a conjugative tcpH gene of C. perfringens plasmid pCPF4969 amplified identical size fragments from a majority of strains tested; and this gene hybridized to the various-sized plasmids of these strains. The sequences of the PCR-amplified tcpH genes from 12 strains showed diversity among the tcpH genes. Regardless of the sources of the isolates, the genetic diversity of C. perfringens extended to the plasmids carrying conjugative genes. Published by Elsevier Ltd.

Multi-locus variable-number tandem repeat analysis of Chinese Brucella strains isolated from 1953 to 2013.

PubMed

Tian, Guo-Zhong; Cui, Bu-Yun; Piao, Dong-Ri; Zhao, Hong-Yan; Li, Lan-Yu; Liu, Xi; Xiao, Pei; Zhao, Zhong-Zhi; Xu, Li-Qing; Jiang, Hai; Li, Zhen-Jun

2017-05-02

Brucellosis was a common human and livestock disease caused by Brucella strains, the category B priority pathogens by the US Center for Disease Control (CDC). Identified as a priority disease in human and livestock populations, the increasing incidence in recent years in China needs urgent control measures for this disease but the molecular background important for monitoring the epidemiology of Brucella strains at the national level is still lacking. A total of 600 Brucella isolates collected during 60 years (from 1953 to 2013) in China were genotyped by multiple locus variable-number tandem repeat analysis (MLVA) and the variation degree of MLVA11 loci was calculated by the Hunter Gaston Diversity Index (HGDI) values. The charts and map were processed by Excel 2013, and cluster analysis and epidemiological distribution was performed using BioNumerics (version 5.1). The 600 representative Brucella isolates fell into 104 genotypes with 58 singleton genotypes by the MLVA11 assay, including B. melitensis biovars 2 and 3 (five main genotypes), B. abortus biovars 1 and 3 (two main genotypes), B. suis biovars 1 and 3 (three main genotypes), and B. canis (two main genotypes) respectively. While most B. suis biovar 1 and biovar 3 were respectively found in northern provinces and southern provinces, B. melitensis and B. abortus strains were dominant in China. Canine Brucellosis was only found in animals without any human cases reported. Eight Brucellosis epidemic peaks emerged during the 60 years between 1953 and 2013: 1955 - 1959, 1962 - 1969, 1971 - 1975, 1977 - 1983, 1985 - 1989, 1992 - 1997, 2000 - 2008 and 2010 - 2013 in China. Brucellosis has its unique molecular epidemiological patterns with specific spatial and temporal distribution according to MLVA. IDOP-D-16-00101.

Phage and MLVA typing of Salmonella enteritidis isolated from layers and humans in Belgium from 2000-2010, a period in which vaccination of laying hens was introduced.

PubMed

Dewaele, I; Heyndrickx, M; Rasschaert, G; Bertrand, S; Wildemauwe, C; Wattiau, P; Imberechts, H; Herman, L; Ducatelle, R; Van Weyenberg, S; De Reu, K

2014-09-01

The aim of the study was to characterize isolates of Salmonella enterica serovar Enteritidis (S. Enteritidis) obtained from humans and layer farms in Belgium collected during 2000-2010. Three periods were compared, namely (i) before implementation of vaccination (2000-2004), (ii) during voluntary vaccination (2005-2006) and (iii) during implementation of the national control program (NCP) for Salmonella including mandatory vaccination against S. Enteritidis (2007-2010). The characteristics compared across time periods were distributions of phage type and multiple-locus variable number tandem-repeat assay (MLVA). While PT4 and PT21 were predominantly isolated in Belgium in layers and humans before 2007, a significant reduction of those PTs was observed in both populations in the period 2007-2010. The relative proportion of PT4b, PT21c and PT6c was found to have increased considerably in the layer population since 2007. In the human population, PT8, PT1 and the group of 'other' PTs were more frequently isolated compared to the previous periods. When comparing the proportion of the predominant MLVA types Q2 and U2, no significant difference was found between the layer and human population in the three periods and between periods within each category (layer and human). A significant difference in isolate distribution among MLVA clusters I and II was found between human and layer isolates recovered during Period 3 and in the human population between Period 1 and 3. Results suggest that the association between S. Enteritidis in layers and the occurrence of the pathogen in humans changed since implementation of the NCP in 2007. © 2013 Blackwell Verlag GmbH.

Development of a Multiple-Locus Variable number of tandem repeat Analysis (MLVA) for Leptospira interrogans and its application to Leptospira interrogans serovar Australis isolates from Far North Queensland, Australia

PubMed Central

Slack, Andrew T; Dohnt, Michael F; Symonds, Meegan L; Smythe, Lee D

2005-01-01

Background Leptospirosis is a zoonotic disease caused by the genus, Leptospira. Leptospira interrogans is the most common genomospecies implicated in the disease. Epidemiological investigations are needed to distinguish outbreak situations or to trace reservoirs of the organisms. Current methodologies used for typing Leptospira have significant drawbacks. The development of an easy to perform yet high resolution method is needed for this organism. Methods In this study we have searched the available genomic sequence of L. interrogans serovar Copenhageni strain Fiocruz L1-130 for the presence of tandem repeats [1]. These repeats were evaluated against reference strains for diversity. Six loci were selected to create a Multiple Locus Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) to explore the genetic diversity within L. interrogans serovar Australis clinical isolates from Far North Queensland. Results The 39 reference strains used for the development of the method displayed 39 distinct patterns. Diversity Indexes for the loci varied between 0.80 and 0.93 and the number of repeat units at each locus varied between less than one to 52 repeats. When the MLVA was applied to serovar Australis isolates three large clusters were distinguishable, each comprising various hosts including Rattus species, human and canines. Conclusion The MLVA described in this report, was easy to perform, analyse and was reproducible. The loci selected had high diversity allowing discrimination between serovars and also between strains within a serovar. This method provides a starting point on which improvements to the method and comparisons to other techniques can be made. PMID:15987533

Verocytotoxigenic Escherichia coli O157 in beef and sheep abattoirs in Ireland and characterisation of isolates by Pulsed-Field Gel Electrophoresis and Multi-Locus Variable Number of Tandem Repeat Analysis.

PubMed

Prendergast, Deirdre M; Lendrum, Lynsey; Pearce, Rachel; Ball, Caroline; McLernon, Joanne; O'Grady, Don; Scott, Lourda; Fanning, Seamus; Egan, John; Gutierrez, Montserrat

2011-01-05

This study aimed to investigate verocytotoxigenic Escherichia coli O157 in the largest beef and sheep slaughter plants in Ireland over a one-year period. Samples consisted of pooled rectal swabs (n=407) and pooled carcass swabs (n=407) from 5 animals belonging to the same herd or flock and minced meat (n=91) from the same sampling date. E. coli O157 isolates were characterised using PCR for a range of genes, i.e. 16S, rfbE, fliC, vtx1, vtx2, eaeA and confirmed VTEC O157 isolates were tested for antimicrobial susceptibility and typed using Pulsed-Field Gel Electrophoresis (PFGE) and Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA). VTEC O157 was isolated from 7.6% and 3.9% of bovine rectal and carcass swab samples and from 5.8% and 2.9% of ovine rectal and carcass swab samples respectively. None of the bovine minced meat samples (n=77) and only one of the 14 ovine minced meat samples was positive for VTEC O157. Following PFGE and MLVA, cross contamination from faeces to carcasses was identified. While PFGE and MLVA identified the same clusters for highly related strains, MLVA discriminated better than PFGE in addition to being more rapid and less labour intensive. Results showed that cattle and sheep presented for slaughter in Ireland harbour VTEC O157, and although the levels entering the food chain are low, this should not be overlooked as possible sources of zoonotic infection; molecular typing was able to demonstrate relationships among strains and could be used to elucidate the sources of human infection. Copyright © 2010 Elsevier B.V. All rights reserved.

Molecular typing of Argentinian Mycobacterium avium subsp. paratuberculosis isolates by multiple-locus variable number-tandem repeat analysis

PubMed Central

Gioffré, Andrea; Correa Muñoz, Magnolia; Alvarado Pinedo, María F.; Vaca, Roberto; Morsella, Claudia; Fiorentino, María Andrea; Paolicchi, Fernando; Ruybal, Paula; Zumárraga, Martín; Travería, Gabriel E.; Romano, María Isabel

2015-01-01

Multiple-locus variable number-tandem repeat analysis (MLVA) of Mycobacterium avium subspecies paratuberculosis (MAP) isolates may contribute to the knowledge of strain diversity in Argentina. Although the diversity of MAP has been previously investigated in Argentina using IS900-RFLP, a small number of isolates were employed, and a low discriminative power was reached. The aim of the present study was to test the genetic diversity among MAP isolates using an MLVA approach based on 8 repetitive loci. We studied 97 isolates from cattle, goat and sheep and could describe 7 different patterns: INMV1, INMV2, INMV11, INMV13, INMV16, INMV33 and one incomplete pattern. INMV1 and INMV2 were the most frequent patterns, grouping 76.3% of the isolates. We were also able to demonstrate the coexistence of genotypes in herds and co-infection at the organism level. This study shows that all the patterns described are common to those described in Europe, suggesting an epidemiological link between the continents. PMID:26273274

DNA fingerprinting of Shiga-toxin producing Escherichia coli O157 based on Multiple-Locus Variable-Number Tandem-Repeats Analysis (MLVA)

PubMed Central

Lindstedt, Bjørn-Arne; Heir, Even; Gjernes, Elisabet; Vardund, Traute; Kapperud, Georg

2003-01-01

Background The ability to react early to possible outbreaks of Escherichia coli O157:H7 and to trace possible sources relies on the availability of highly discriminatory and reliable techniques. The development of methods that are fast and has the potential for complete automation is needed for this important pathogen. Methods In all 73 isolates of shiga-toxin producing E. coli O157 (STEC) were used in this study. The two available fully sequenced STEC genomes were scanned for tandem repeated stretches of DNA, which were evaluated as polymorphic markers for isolate identification. Results The 73 E. coli isolates displayed 47 distinct patterns and the MLVA assay was capable of high discrimination between the E. coli O157 strains. The assay was fast and all the steps can be automated. Conclusion The findings demonstrate a novel high discriminatory molecular typing method for the important pathogen E. coli O157 that is fast, robust and offers many advantages compared to current methods. PMID:14664722

Multiple-locus variable number of tandem repeat analysis as a tool for molecular epidemiology of botulism: The Italian experience.

PubMed

Anniballi, Fabrizio; Fillo, Silvia; Giordani, Francesco; Auricchio, Bruna; Tehran, Domenico Azarnia; di Stefano, Enrica; Mandarino, Giuseppina; De Medici, Dario; Lista, Florigio

2016-12-01

Clostridium botulinum is the bacterial agent of botulism, a rare but severe neuro-paralytic disease. Because of its high impact, in Italy botulism is monitored by an ad hoc surveillance system. The National Reference Centre for Botulism, as part of this system, collects and analyzes all demographic, epidemiologic, microbiological, and molecular data recovered during cases and/or outbreaks occurred in Italy. A panel of 312 C. botulinum strains belonging to group I were submitted to MLVA sub-typing. Strains, isolated from clinical specimens, food and environmental samples collected during the surveillance activities, were representative of all forms of botulism from all Italian regions. Through clustering analysis isolates were grouped into 12 main clusters. No regional or temporal clustering was detected, demonstrating the high heterogeneity of strains circulating in Italy. This study confirmed that MLVA is capable of sub-typing C. botulinum strains. Moreover, MLVA is effective at tracing and tracking the source of contamination and is helpful for the surveillance system in terms of planning and upgrading of procedures, activities and data collection forms. Copyright © 2016 Elsevier B.V. All rights reserved.

New paradigms for Salmonella source attribution based on microbial subtyping.

PubMed

Mughini-Gras, Lapo; Franz, Eelco; van Pelt, Wilfrid

2018-05-01

Microbial subtyping is the most common approach for Salmonella source attribution. Typically, attributions are computed using frequency-matching models like the Dutch and Danish models based on phenotyping data (serotyping, phage-typing, and antimicrobial resistance profiling). Herewith, we critically review three major paradigms facing Salmonella source attribution today: (i) the use of genotyping data, particularly Multi-Locus Variable Number of Tandem Repeats Analysis (MLVA), which is replacing traditional Salmonella phenotyping beyond serotyping; (ii) the integration of case-control data into source attribution to improve risk factor identification/characterization; (iii) the investigation of non-food sources, as attributions tend to focus on foods of animal origin only. Population genetics models or simplified MLVA schemes may provide feasible options for source attribution, although there is a strong need to explore novel modelling options as we move towards whole-genome sequencing as the standard. Classical case-control studies are enhanced by incorporating source attribution results, as individuals acquiring salmonellosis from different sources have different associated risk factors. Thus, the more such analyses are performed the better Salmonella epidemiology will be understood. Reparametrizing current models allows for inclusion of sources like reptiles, the study of which improves our understanding of Salmonella epidemiology beyond food to tackle the pathogen in a more holistic way. Copyright © 2017 Elsevier Ltd. All rights reserved.

Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014.

PubMed

Phillips, Anastasia; Sotomayor, Cristina; Wang, Qinning; Holmes, Nadine; Furlong, Catriona; Ward, Kate; Howard, Peter; Octavia, Sophie; Lan, Ruiting; Sintchenko, Vitali

2016-09-15

Salmonella Typhimurium (STM) is an important cause of foodborne outbreaks worldwide. Subtyping of STM remains critical to outbreak investigation, yet current techniques (e.g. multilocus variable number tandem repeat analysis, MLVA) may provide insufficient discrimination. Whole genome sequencing (WGS) offers potentially greater discriminatory power to support infectious disease surveillance. We performed WGS on 62 STM isolates of a single, endemic MLVA type associated with two epidemiologically independent, food-borne outbreaks along with sporadic cases in New South Wales, Australia, during 2014. Genomes of case and environmental isolates were sequenced using HiSeq (Illumina) and the genetic distance between them was assessed by single nucleotide polymorphism (SNP) analysis. SNP analysis was compared to the epidemiological context. The WGS analysis supported epidemiological evidence and genomes of within-outbreak isolates were nearly identical. Sporadic cases differed from outbreak cases by a small number of SNPs, although their close relationship to outbreak cases may represent an unidentified common food source that may warrant further public health follow up. Previously unrecognised mini-clusters were detected. WGS of STM can discriminate foodborne community outbreaks within a single endemic MLVA clone. Our findings support the translation of WGS into public health laboratory surveillance of salmonellosis.

Molecular characterization by MLVA of Coxiella burnetii strains infecting dairy cows and goats of north-eastern Italy.

PubMed

Ceglie, Letizia; Guerrini, Eulalia; Rampazzo, Erika; Barberio, Antonio; Tilburg, Jeroen J H C; Hagen, Ferry; Lucchese, Laura; Zuliani, Federica; Marangon, Stefano; Natale, Alda

2015-01-01

Q fever is a worldwide zoonotic disease caused by Coxiella burnetii (C. burnetii), an obligate intracellular bacterium. In ruminants, shedding into the environment mainly occurs during parturition or abortion, but the bacterium is shed also in milk, vaginal mucus, stools and urine. In Italy few surveys have been conducted and reported seroprevalence values ranged between 10% and 60%, even if few human cases have been described. Genotyping of bacteria is crucial for enhancing diagnostic methods and for epidemiological surveillance. The objective of this study was to investigate genotypic differences of C. burnetii genotypes directly in 34 samples, collected during a 3-years survey among 11 dairy cattle and 11 goat farms in the north-eastern part of Italy using a 6-locus multiple loci variable number of tandem repeat analysis (MLVA) method. The samples analysed included 13 bulk tank milk (BTM), 6 individual milk, 11 vaginal swabs and 4 foetal spleens. MLVA-type 2 was determined as the most prevalent in cattle in this study. C. burnetii strains circulating in the studied cattle population are very similar to genotypes previously described, while genotypes from goats showed an important variability. Further investigation are needed to understand the reason of this pattern. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Genotyping of Pseudomonas aeruginosa isolates from lung transplant recipients and aquatic environment-detected in-hospital transmission.

PubMed

Johansson, Ewa; Welinder-Olsson, Christina; Gilljam, Marita

2014-02-01

Lung infection with Pseudomonas aeruginosa is common in lung transplant recipients and may lead to severe complications. Bacteriological surveillance aims to detect transmission of microbes between hospital environment and patients. We sought to determine whether genotyping of P. aeruginosa isolates could improve identifications of pathways of infection. From 2004 to 2009, we performed genotyping with multiple-locus variable number of tandem repeats analysis (MLVA) and pulsed-field gel electrophoresis (PFGE) of P. aeruginosa isolates cultured from lung transplant recipients at Sahlgrenska University Hospital, Gothenburg. During a small outbreak in 2008, cultivation and genotyping of isolates from sink and drains samples from the hospital ward were performed. Pseudomona aeruginosa from 11/18 patients were genotyped to unique strains. The remaining seven patients were carriers of a P. aeruginosa strain of cluster A genotype. Pseudomona aeruginosa was isolated in 4/8 water samples, typed by MLVA also as cluster A genotype and confirmed by PFGE to be similar or identical to the isolates from four transplanted patients. In conclusion, genotyping of isolates revealed a clonal relationship between patient and water isolates, indicating in-hospital transmission of P. aeruginosa. We suggest genotyping with MLVA for rapid routine surveillance, with the PFGE method used for extended, confirmatory analyses. © 2013 APMIS. Published by John Wiley & Sons Ltd.

Whole genome sequencing of Brucella melitensis isolated from 57 patients in Germany reveals high diversity in strains from Middle East

PubMed Central

Georgi, Enrico; Walter, Mathias C.; Pfalzgraf, Marie-Theres; Northoff, Bernd H.; Holdt, Lesca M.; Scholz, Holger C.; Zoeller, Lothar

2017-01-01

Brucellosis, a worldwide common bacterial zoonotic disease, has become quite rare in Northern and Western Europe. However, since 2014 a significant increase of imported infections caused by Brucella (B.) melitensis has been noticed in Germany. Patients predominantly originated from Middle East including Turkey and Syria. These circumstances afforded an opportunity to gain insights into the population structure of Brucella strains. Brucella-isolates from 57 patients were recovered between January 2014 and June 2016 with culture confirmed brucellosis by the National Consultant Laboratory for Brucella. Their whole genome sequences were generated using the Illumina MiSeq platform. A whole genome-based SNP typing assay was developed in order to resolve geographically attributed genetic clusters. Results were compared to MLVA typing results, the current gold-standard of Brucella typing. In addition, sequences were examined for possible genetic variation within target regions of molecular diagnostic assays. Phylogenetic analyses revealed spatial clustering and distinguished strains from different patients in either case, whereas multiple isolates from a single patient or technical replicates showed identical SNP and MLVA profiles. By including WGS data from the NCBI database, five major genotypes were identified. Notably, strains originating from Turkey showed a high diversity and grouped into seven subclusters of genotype II. MLVA analysis congruently clustered all isolates and predominantly matched the East Mediterranean genetic clade. This study confirms whole-genome based SNP-analysis as a powerful tool for accurate typing of B. melitensis. Furthermore it allows special allocation and therefore provides useful information on the geographic origin for trace-back analysis. However, the lack of reliable metadata in public databases often prevents a resolution below geographic regions or country levels and corresponding precise trace-back analysis. Once this obstacle is resolved, WGS-derived bacterial typing adds an important method to complement epidemiological surveys during outbreak investigations. This is the first report of a detailed genetic investigation of an extensive collection of B. melitensis strains isolated from human cases in Germany. PMID:28388689

Tolerance to quaternary ammonium compound disinfectants may enhance growth of Listeria monocytogenes in the food industry.

PubMed

Møretrø, Trond; Schirmer, Bjørn C T; Heir, Even; Fagerlund, Annette; Hjemli, Pernille; Langsrud, Solveig

2017-01-16

The antibacterial effect of disinfectants is crucial for the control of Listeria monocytogenes in food processing environments. Tolerance of L. monocytogenes to sublethal levels of disinfectants based on quaternary ammonium compounds (QAC) is conferred by the resistance determinants qacH and bcrABC. The presence and distribution of these genes have been anticipated to have a role in the survival and growth of L. monocytogenes in food processing environments where QAC based disinfectants are in common use. In this study, a panel of 680 L. monocytogenes from nine Norwegian meat- and salmon processing plants were grouped into 36 MLVA profiles. The presence of qacH and bcrABC was determined in 101 isolates from the 26 most common MLVA profiles. Five MLVA profiles contained qacH and two contained bcrABC. Isolates with qacH and bcrABC showed increased tolerance to the QAC Benzalkonium chloride (BC), with minimal inhibitory concentrations (MICs) of 5-12, 10-13 and <5ppm for strains with qacH (two allele variants observed), bcrABC, and neither gene, respectively. Isolates with qacH or bcrABC were not more tolerant to BC in bactericidal tests in suspension or in biofilms compared with isolates lacking the genes. Water residue samples collected from surfaces in meat processing plants after QAC disinfection had bactericidal effect against L. monocytogenes when the sample BC levels were high (>100ppm). A sample with lower BC concentrations (14ppm of chain length C-12 and 2.7ppm of chain length C-14) inhibited growth of L. monocytogenes not containing bcrABC or qacH, compared to strains with these genes. The study has shown that L. monocytogenes harbouring the QAC resistance genes qacH and bcrABC are prevalent in the food industry and that residuals of QAC may be present in concentrations after sanitation in the industry that result in a growth advantage for bacteria with such resistance genes. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Listeria monocytogenes Circulating in Rabbit Meat Products and Slaughterhouses in Italy: Prevalence Data and Comparison Among Typing Results.

PubMed

De Cesare, Alessandra; Parisi, Antonio; Mioni, Renzo; Comin, Damiano; Lucchi, Alex; Manfreda, Gerardo

2017-03-01

Rabbit meat has outstanding dietetic and nutritional properties. However, few data on microbiological hazards associated with rabbit productions are available. In this study, the presence of Listeria monocytogenes was determined in 430 rabbit carcasses, 256 rabbit meat cuts and products, and 599 environmental sponges collected from four Italian rabbit slaughterhouses over a period of 1 year. Prevalence of L. monocytogenes among the 1285 rabbit meat and environmental samples was 11%, with statistically significant differences between slaughterhouses. The highest prevalence (33.6%) was observed in rabbit meat cuts and products; the majority of positive environmental samples were collected from conveyor belts. Overall, 27.9% and 14.3% of rabbit cuts and carcasses, respectively, had L. monocytogenes counts higher than 1 colony-forming unit (CFU)/10 g. A selection of 123 isolates from positive samples was genotyped and serotyped to determine genetic profiles and diversity among L. monocytogenes isolates contaminating different slaughterhouses and classes of products investigated. Discriminatory power and concordance among the results obtained using multilocus variable-number tandem-repeat analysis (MLVA), multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), automated EcoRI ribotyping, and serotyping were assessed. The isolates selected for typing were classified into serotypes 1/2a (52.8%), 1/2c (32.5%), and 1/2b (14.6%). The majority of the isolates were classified as ST14 (34.1%), ST9 (35.5%), ST121 (17.9%), and ST224 (14.6%). The greatest discriminatory power was observed with the MLVA typing, followed by MLST, PFGE, and ribotyping. The best bidirectional concordance was achieved between PFGE and MLST. There was 100% correlation between both MLST and MLVA with serotype. Moreover, a high unidirectional correspondence was observed between MLVA and both MLST and PFGE, as well as between PFGE and both MLST and serotyping. The results of this study show for the first time in Italy prevalence and genetic profiles of L. monocytogenes isolated in rabbit products and slaughterhouses.

Multilocus Variable-Number-Tandem-Repeats Analysis (MLVA) distinguishes a clonal complex of Clavibacter michiganensis subsp. michiganensis strains isolated from recent outbreaks of bacterial wilt and canker in Belgium

PubMed Central

2013-01-01

Background Clavibacter michiganensis subsp. michiganensis (Cmm) causes bacterial wilt and canker in tomato. Cmm is present nearly in all European countries. During the last three years several local outbreaks were detected in Belgium. The lack of a convenient high-resolution strain-typing method has hampered the study of the routes of transmission of Cmm and epidemiology in tomato cultivation. In this study the genetic relatedness among a worldwide collection of Cmm strains and their relatives was approached by gyrB and dnaA gene sequencing. Further, we developed and applied a multilocus variable number of tandem repeats analysis (MLVA) scheme to discriminate among Cmm strains. Results A phylogenetic analysis of gyrB and dnaA gene sequences of 56 Cmm strains demonstrated that Belgian Cmm strains from recent outbreaks of 2010–2012 form a genetically uniform group within the Cmm clade, and Cmm is phylogenetically distinct from other Clavibacter subspecies and from non-pathogenic Clavibacter-like strains. MLVA conducted with eight minisatellite loci detected 25 haplotypes within Cmm. All strains from Belgian outbreaks, isolated between 2010 and 2012, together with two French strains from 2010 seem to form one monomorphic group. Regardless of the isolation year, location or tomato cultivar, Belgian strains from recent outbreaks belonged to the same haplotype. On the contrary, strains from diverse geographical locations or isolated over longer periods of time formed mostly singletons. Conclusions We hypothesise that the introduction might have originated from one lot of seeds or contaminated tomato seedlings that was the source of the outbreak in 2010 and that these Cmm strains persisted and induced infection in 2011 and 2012. Our results demonstrate that MLVA is a promising typing technique for a local surveillance and outbreaks investigation in epidemiological studies of Cmm. PMID:23738754

Multilocus variable-number-tandem-repeats analysis (MLVA) distinguishes a clonal complex of Clavibacter michiganensis subsp. michiganensis strains isolated from recent outbreaks of bacterial wilt and canker in Belgium.

PubMed

Zaluga, Joanna; Stragier, Pieter; Van Vaerenbergh, Johan; Maes, Martine; De Vos, Paul

2013-06-05

Clavibacter michiganensis subsp. michiganensis (Cmm) causes bacterial wilt and canker in tomato. Cmm is present nearly in all European countries. During the last three years several local outbreaks were detected in Belgium. The lack of a convenient high-resolution strain-typing method has hampered the study of the routes of transmission of Cmm and epidemiology in tomato cultivation. In this study the genetic relatedness among a worldwide collection of Cmm strains and their relatives was approached by gyrB and dnaA gene sequencing. Further, we developed and applied a multilocus variable number of tandem repeats analysis (MLVA) scheme to discriminate among Cmm strains. A phylogenetic analysis of gyrB and dnaA gene sequences of 56 Cmm strains demonstrated that Belgian Cmm strains from recent outbreaks of 2010-2012 form a genetically uniform group within the Cmm clade, and Cmm is phylogenetically distinct from other Clavibacter subspecies and from non-pathogenic Clavibacter-like strains. MLVA conducted with eight minisatellite loci detected 25 haplotypes within Cmm. All strains from Belgian outbreaks, isolated between 2010 and 2012, together with two French strains from 2010 seem to form one monomorphic group. Regardless of the isolation year, location or tomato cultivar, Belgian strains from recent outbreaks belonged to the same haplotype. On the contrary, strains from diverse geographical locations or isolated over longer periods of time formed mostly singletons. We hypothesise that the introduction might have originated from one lot of seeds or contaminated tomato seedlings that was the source of the outbreak in 2010 and that these Cmm strains persisted and induced infection in 2011 and 2012. Our results demonstrate that MLVA is a promising typing technique for a local surveillance and outbreaks investigation in epidemiological studies of Cmm.

Comparison of seven techniques for typing international epidemic strains of Clostridium difficile: restriction endonuclease analysis, pulsed-field gel electrophoresis, PCR-ribotyping, multilocus sequence typing, multilocus variable-number tandem-repeat analysis, amplified fragment length polymorphism, and surface layer protein A gene sequence typing.

PubMed

Killgore, George; Thompson, Angela; Johnson, Stuart; Brazier, Jon; Kuijper, Ed; Pepin, Jacques; Frost, Eric H; Savelkoul, Paul; Nicholson, Brad; van den Berg, Renate J; Kato, Haru; Sambol, Susan P; Zukowski, Walter; Woods, Christopher; Limbago, Brandi; Gerding, Dale N; McDonald, L Clifford

2008-02-01

Using 42 isolates contributed by laboratories in Canada, The Netherlands, the United Kingdom, and the United States, we compared the results of analyses done with seven Clostridium difficile typing techniques: multilocus variable-number tandem-repeat analysis (MLVA), amplified fragment length polymorphism (AFLP), surface layer protein A gene sequence typing (slpAST), PCR-ribotyping, restriction endonuclease analysis (REA), multilocus sequence typing (MLST), and pulsed-field gel electrophoresis (PFGE). We assessed the discriminating ability and typeability of each technique as well as the agreement among techniques in grouping isolates by allele profile A (AP-A) through AP-F, which are defined by toxinotype, the presence of the binary toxin gene, and deletion in the tcdC gene. We found that all isolates were typeable by all techniques and that discrimination index scores for the techniques tested ranged from 0.964 to 0.631 in the following order: MLVA, REA, PFGE, slpAST, PCR-ribotyping, MLST, and AFLP. All the techniques were able to distinguish the current epidemic strain of C. difficile (BI/027/NAP1) from other strains. All of the techniques showed multiple types for AP-A (toxinotype 0, binary toxin negative, and no tcdC gene deletion). REA, slpAST, MLST, and PCR-ribotyping all included AP-B (toxinotype III, binary toxin positive, and an 18-bp deletion in tcdC) in a single group that excluded other APs. PFGE, AFLP, and MLVA grouped two, one, and two different non-AP-B isolates, respectively, with their AP-B isolates. All techniques appear to be capable of detecting outbreak strains, but only REA and MLVA showed sufficient discrimination to distinguish strains from different outbreaks.

Characterization of Shigella sonnei isolates from travel-associated cases in Japan.

PubMed

Izumiya, Hidemasa; Tada, Yuki; Ito, Kenichiro; Morita-Ishihara, Tomoko; Ohnishi, Makoto; Terajima, Jun; Watanabe, Haruo

2009-11-01

Shigella sonnei infection in industrialized countries is often associated with foreign travel. A total of 195 S. sonnei isolates in Japan, isolated from cases associated with foreign travel, were analysed by biotyping and molecular typing using PFGE and multilocus variable-number tandem-repeat analysis (MLVA); their antimicrobial susceptibilities were also evaluated. The isolates were from 26 countries, most of which were Asian. Molecular typing revealed a correlation among the genotypes, biotypes and their geographical areas of origin. The isolates were classified into two biotypes, a and g. Biotype g isolates (n=178) were further divided into distinct clusters mainly on the basis of their geographical areas of origin by both PFGE and MLVA. Isolates from South Asian countries constituted one of the distinct clusters. Biotype g isolates from countries other than South Asia constituted other distinct clusters. Most of the isolates from other countries and continents, excluding the South Asian countries, were included in one major cluster by PFGE analysis. However, by MLVA, they were further divided into minor subclusters mainly on the basis of their countries of origin. MLVA was also demonstrated to be useful in molecular epidemiological analysis, even when only seven loci were applied, resulting in a high resolution with Simpson's index of diversity (D) of 0.993. A core drug-resistance pattern of streptomycin, sulfisoxazole, tetracycline and trimethoprim-sulfamethoxazole was observed in 108 isolates, irrespective of their geographical areas of origin, but the frequency of resistance to nalidixic acid was high among the South Asian and East Asian isolates. Two isolates from China and India were resistant to cefotaxime and harboured the bla(CTX-M-14) and bla(CTX-M-15) genes, respectively; these isolates were also resistant to nalidixic acid, which is a matter of concern in terms of shigellosis treatment. Use of a combination of methods was found to be effective for epidemiological investigation in the case of S. sonnei infection.

Prevalence, genetic relatedness and antibiotic resistance of hospital-acquired clostridium difficile PCR ribotype 018 strains.

PubMed

Seo, Mi-Ran; Kim, Jieun; Lee, Yangsoon; Lim, Dong-Gyun; Pai, Hyunjoo

2018-05-01

Clostridium difficile infection (CDI) is a major healthcare-associated infection. The aim of this study was to investigate the genetic relatedness of the endemic C. difficile PCR ribotype 018 strains in an institution and changes to their characteristics during a five-year period. A total of 207 isolates from inpatients at Hanyang University Hospital from 2009 to 2013 were analysed using multilocus variable-number tandem-repeat analysis (MLVA). Minimum inhibitory concentrations (MICs) of several antibiotics were determined. In total, 204 (98.6%) were genetically related, with a summed tandem-repeat distance (STRD) ≤ 10. Minimum-spanning-tree analysis identified 78 MLVA types, categorized into six clonal complexes (CCs). The largest cluster, CC-I, included 51 MLVA types from 148 isolates (71.5%) and the second largest cluster, CC-II, included 10 MLVA types from 36 isolates (17.4%). Resistance rates for antibiotics were: clindamycin (CLI), 97.6%; moxifloxacin (MXF), 98.6%; vancomycin (VAN), 1.4%; and rifaximin (RFX), 8.2%. All isolates were susceptible to piperacillin/tazobactam (TZP) and metronidazole (MTZ). Comparing the MICs of antibiotics for the isolates each year from 2009 to 2013, MICs of antibiotics that promote CDI, such as CLI, MXF, TZP and RFX, increased over the five-year period (P-value by Kruskal-Wallis test: < 0.0001, <0.0001, <0.0001, and <0.0001 respectively); however, MICs of VAN or MTZ, antibiotics for treatment of CDI, did not increase or decreased over the same time period (P-value by Kruskal-Wallis test: 0.166, <0.0001). C. difficile RT018 isolates in a tertiary hospital over a five-year period presented a close clonal relationship. MICs of antibiotics promoting CDI increased with this clonal expansion. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

[Report of Relapse Typhoid Fever Cases from Kolkata, India: Recrudescence or Reinfection?

PubMed

Samajpati, Sriparna; Das, Surojit; Ray, Ujjwayini; Dutta, Shanta

2018-05-24

Three relapse cases were reported out of 107 hospital-attending typhoid cases within a period of 2 years (2014-2016) from Apollo Gleneagles Hospital, Kolkata, India. During the first episode of typhoid fever, 2 of the 3 cases were treated with ceftriaxone (CRO) for 7 days, and 1 was treated for 14 days. Six Salmonella Typhi (S. Typhi) isolates, obtained from the 3 patients during both typhoid episodes, were subjected to antimicrobial susceptibility testing, detection of quinolone resistance-determining region (QRDR) mutation and molecular subtyping by pulsed-field gel electrophoresis (PFGE), multiple-locus variable number tandem repeat analysis (MLVA), multilocus sequence typing (MLST), clustered regularly interspaced short palindromic repeats (CRISPR), and H58 haplotyping. Pairs of the S. Typhi strains isolated from two of the patients during the 1st and 2nd episodes were similar with respect to the antimicrobial resistance (AMR) profiles, QRDR mutations, and molecular subtypes; whereas, the S. Typhi strain pair isolated from the 3rd patient were different in their AMR profiles, QRDR mutations, and MLVA profiles. From these observations, it may be concluded that in spite of treating typhoid cases with CRO for 7-14 days, relapse of typhoid fever might occur. The article also showed the advantage of MLVA typing over PFGE, MLST, and CRISPR typing for the discrimination of strains isolated from the same patient in case of relapse of typhoid fever.

Phylogenetic Characteristics of Anthrax Outbreaks in Liaoning Province, China, 2001-2015.

PubMed

Mao, Lingling; Zhang, Enmin; Wang, Zijiang; Li, Yan; Zhou, Hang; Liu, Xuesheng; Zhang, Huijuan; Cai, Hong; Liang, Xudong; Sun, Yingwei; Zhang, Zhikai; Li, Wei; Yao, Wenqing; Wei, Jianchun

2016-01-01

Anthrax is a continuous threat in China, especially in rural regions. In July 2015, an anthrax outbreak occurred in Xifeng County, Liaoning Province. A total of 10 cutaneous anthrax cases were reported, with 210 people under medical observation. In this study, the general characteristics of human anthrax outbreak occurred in Liaoning Province were described, and all cases were caused by butchering and contacting sick animal. Meanwhile, the phylogenetic relationship between outbreak-related isolates/samples of the year 2015 and previous Bacillus anthracis strains was analyzed by means of canonical single nucleotide polymorphisms (canSNP), multiple-locus variable-number tandem repeat analysis (MLVA) with 15 markers and single-nucleotide repeats (SNR) analysis. There are two canSNP subgroups found in Liaoning, A.Br.001/002 and A.Br.Ames, and a total of six MLVA 15 genotypes and five SNR genotypes were observed. The strain collected from anthrax outbreak in Xifeng County in 2015 was classified as A.Br.001/002 subgroup and identified as MLVA15-29 genotype, with same SNR profile (CL10: 17, CL12: 15, CL33: 29, and CL35: 13). So we conclude that the same clone of B.anthracis caused the anthrax outbreak in Xifeng County in 2015, and this clone is different to previous isolates. Strengthening public health education in China is one of the most important measures to prevent and control anthrax.

Multiple locus VNTR analysis highlights that geographical clustering and distribution of Dichelobacter nodosus, the causal agent of footrot in sheep, correlates with inter-country movements☆

PubMed Central

Russell, Claire L.; Smith, Edward M.; Calvo-Bado, Leonides A.; Green, Laura E.; Wellington, Elizabeth M.H.; Medley, Graham F.; Moore, Lynda J.; Grogono-Thomas, Rosemary

2014-01-01

Dichelobacter nodosus is a Gram-negative, anaerobic bacterium and the causal agent of footrot in sheep. Multiple locus variable number tandem repeat (VNTR) analysis (MLVA) is a portable technique that involves the identification and enumeration of polymorphic tandem repeats across the genome. The aims of this study were to develop an MLVA scheme for D. nodosus suitable for use as a molecular typing tool, and to apply it to a global collection of isolates. Seventy-seven isolates selected from regions with a long history of footrot (GB, Australia) and regions where footrot has recently been reported (India, Scandinavia), were characterised. From an initial 61 potential VNTR regions, four loci were identified as usable and in combination had the attributes required of a typing method for use in bacterial epidemiology: high discriminatory power (D > 0.95), typeability and reproducibility. Results from the analysis indicate that D. nodosus appears to have evolved via recombinational exchanges and clonal diversification. This has resulted in some clonal complexes that contain isolates from multiple countries and continents; and others that contain isolates from a single geographic location (country or region). The distribution of alleles between countries matches historical accounts of sheep movements, suggesting that the MLVA technique is sufficiently specific and sensitive for an epidemiological investigation of the global distribution of D. nodosus. PMID:23748018

Application of multilocus variable number tandem repeat analysis to monitor Verocytotoxin-producing Escherichia coli O157 phage type 8 in England and Wales: emergence of a profile associated with a national outbreak.

PubMed

Perry, N; Cheasty, T; Dallman, T; Launders, N; Willshaw, G

2013-10-01

Evaluation of multilocus variable number tandem repeat analysis (MLVA) to subtype all isolates of Vero cytotoxin-producing Escherichia coli O157 phage type 8 in England and Wales. Over a 13 month period from December 2010, 483 isolates of VTEC O157 PT8 were tested by MLVA; 39% were received in the first 4 months of 2011, when infections are generally low. One profile, or single locus variants of it, was present in 249 (52%) isolates but was not common previously. These cases represented a national increase in PT8, associated epidemiologically with soil-contaminated vegetables. Most of the 177 other MLVA profiles were unique to a single isolate. Profiles shared by >1 isolate included cases from two small community, food-borne outbreaks and 11 households. Several shared profiles were found among 23 isolates without known links. Apart from one group, isolates linked to travel abroad had very diverse profiles. Multilocus variable number tandem repeat analysis discriminated apparent sporadic isolates of the same PT and assisted in detection of cases in an emerging national outbreak. Multilocus variable number tandem repeat analysis is an epidemiologically valid complement to surveillance and applicable as a rapid, practical test for large numbers of isolates. © 2013 The Society for Applied Microbiology.

Report for the NGFA-5 project.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaing, C; Jackson, P; Thissen, J

The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, TaqMan PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. To effectively compare the sensitivity and specificity of the different genomic technologies, we used SNP TaqMan PCR, MLVA, microarray and high-throughput illumine and 454 sequencing to test various strains from B. anthracis, B. thuringiensis, BioWatch aerosol filter extracts or soil samples that were spiked with B. anthracis, and samples that were previously collected during DHS and EPAmore » environmental release exercises that were known to contain B. thuringiensis spores. The results of all the samples against the various assays are discussed in this report.« less

Metallo-β-lactamase-producing Pseudomonas aeruginosa in the Netherlands: the nationwide emergence of a single sequence type.

PubMed

Van der Bij, A K; Van der Zwan, D; Peirano, G; Severin, J A; Pitout, J D D; Van Westreenen, M; Goessens, W H F

2012-09-01

Recently, the first outbreak of clonally related VIM-2 metallo-β-lactamase (MBL)-producing Pseudomonas aeruginosa in a Dutch tertiary-care centre was described. Subsequently, a nationwide surveillance study was performed in 2010-2011, which identified the presence of VIM-2 MBL-producing P. aeruginosa in 11 different hospitals. Genotyping by multiple-locus variable-number tandem-repeat analysis (MLVA) showed that the majority of the 82 MBL-producing isolates found belonged to a single MLVA type (n = 70, 85%), identified as ST111 by multilocus sequence typing (MLST). As MBL-producing isolates cause serious infections that are difficult to treat, the presence of clonally related isolates in various hospitals throughout the Netherlands is of nationwide concern. © 2012 The Authors. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.

Prolonged and mixed non-O157 Escherichia coli infection in an Australian household.

PubMed

Staples, M; Graham, R M A; Doyle, C J; Smith, H V; Jennison, A V

2012-05-01

An Australian family was identified through a Public Health follow up on a Shiga-toxigenic Escherichia coli (STEC) positive bloody diarrhoea case, with three of the four family members experiencing either symptomatic or asymptomatic STEC shedding. Bacterial isolates were submitted to stx sequence sub-typing, multi-locus variable number tandem repeat analysis (MLVA), multi-locus sequence typing (MLST) and binary typing. The analysis revealed that there were multiple strains of STEC being shed by the family members, with similar virulence gene profiles and the same serogroup but differing in their MLVA and MLST profiles. This study illustrates the potentially complicated nature of non-O157 STEC infections and the importance of molecular epidemiology in understanding disease clusters. © 2012 QUEENSLAND HEALTH. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.

Distribution of virulence genes and genotyping of CTX-M-15-producing Klebsiella pneumoniae isolated from patients with community-acquired urinary tract infection (CA-UTI).

PubMed

Ranjbar, Reza; Memariani, Hamed; Sorouri, Rahim; Memariani, Mojtaba

2016-11-01

Klebsiella pneumoniae is one of the most important agents of community-acquired urinary tract infection (CA-UTI). In addition to extended-spectrum β-lactamases (ESBLs), a number of virulence factors have been shown to play an important role in the pathogenesis of K. pneumoniae, including capsule, siderophores, and adhesins. Little is known about the genetic diversity and virulence content of the CTX-M-15-producing K. pneumoniae isolated from CA-UTI in Iran. A total of 152 K. pneumoniae isolates were collected from CA-UTI patients in Tehran from September 2015 through April 2016. Out of 152 isolates, 40 (26.3%) carried bla CTX-M-15 . PCR was performed for detection of virulence genes in CTX-M-15-producing isolates. Furthermore, all of these isolates were subjected to multiple-locus variable-number of tandem repeat (VNTR) analysis (MLVA). Using MLVA method, 36 types were identified. CTX-M-15-producing K. pneumoniae isolates were grouped into 5 clonal complexes (CCs). Of these isolates, mrkD was the most prevalent virulence gene (95%), followed by kpn (60%), rmpA (37.5%), irp (35%), and magA (2.5%). No correlation between MLVA types or CCs and virulence genes or antibiotic resistance patterns was observed. Overall, it is thought that CTX-M-15-producing K. pneumoniae strains isolated from CA-UTI have arisen from different clones. Copyright © 2016 Elsevier Ltd. All rights reserved.

Public health significance of major genotypes of Salmonella enterica serovar Enteritidis present in both human and chicken isolates in Korea.

PubMed

Kang, Min-Su; Oh, Jae-Young; Kwon, Yong-Kuk; Lee, Deog-Yong; Jeong, Ok-Mi; Choi, Byung-Kook; Youn, So-Youn; Jeon, Byung-Woo; Lee, Hye-Jin; Lee, Hee-Soo

2017-06-01

Salmonella enterica serovar Enteritidis is one of the most common serotypes implicated in Salmonella infections in both humans and poultry worldwide. It has been reported that human salmonellosis is mainly associated with the consumption of poultry products contaminated with serovar Enteritidis. The present study was to extensively analyze the public health risk of serovar Enteritidis isolates from chickens in Korea. A total of 127 chicken isolates were collected from clinical cases, on-farm feces, and chicken meat between 1998 and 2012 and 20 human clinical isolates were obtained from patients with diarrhea between 2000 and 2006 in Korea. To characterize the isolates from chickens and humans, we compared the pulsed-field gel electrophoresis (PFGE) patterns and multilocus variable-number tandem-repeat analysis (MLVA) profiles of the isolates. We further characterized representative isolates of different genotypes using a DNA microarray. PFGE revealed 28 patterns and MLVA identified 16 allelic profiles. The DNA microarray showed high genetic variability in plasmid regions and other fimbrial subunits of the isolates although the virulence gene contents of isolates from the same source and/or of the same genotype were unrelated. PFGE and MLVA showed that major genotypes were present in both human and chicken isolates. This result suggests that chickens in Korea pose a significant risk to public health as a source of serovar Enteritidis as has been noted in other countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

A multi-country Salmonella Enteritidis phage type 14b outbreak associated with eggs from a German producer: 'near real-time' application of whole genome sequencing and food chain investigations, United Kingdom, May to September 2014.

PubMed

Inns, T; Lane, C; Peters, T; Dallman, T; Chatt, C; McFarland, N; Crook, P; Bishop, T; Edge, J; Hawker, J; Elson, R; Neal, K; Adak, G K; Cleary, P

2015-04-23

We report an outbreak of Salmonella Enteritidis phage type 14b (PT14b) in the United Kingdom (UK) between May and September 2014 where Public Health England launched an investigation to identify the source of infection and implement control measures. During the same period, outbreaks caused by a Salmonella Enteritidis strain with a specific multilocus variable-number tandem repeat analysis (MLVA) profile occurred in other European Union Member States. Isolates from a number of persons affected by the UK outbreak, who had initially been tested by MLVA also shared this particular profile. Cases were defined as any person infected with S. Enteritidis PT14b, resident in England or Wales and without history of travel outside of this geographical area during the incubation period, reported from 1 June 2014 onwards, with a MLVA profile of 2–11–9-7–4-3–2-8–9 or a single locus variant thereof. In total, 287 cases met the definition. Food traceback investigations in the UK and other affected European countries linked the outbreaks to chicken eggs from a German company. We undertook whole genome sequencing of isolates from UK and European cases, implicated UK premises, and German eggs: isolates were highly similar. Combined with food traceback information, this confirmed that the UK outbreak was also linked to a German producer.

Genetic characterization of non-O157 verocytotoxigenic Escherichia coli isolated from raw beef products using multiple-locus variable-number tandem repeat analysis.

PubMed

Franci, Tomás; Sanso, A Mariel; Bustamante, Ana V; Lucchesi, Paula M A; Parma, Alberto E

2011-09-01

Verocytotoxigenic Escherichia coli (VTEC) can produce serious human illness linked to the consumption of contaminated food, mainly of bovine origin. There is growing concern about non-O157 VTEC serotypes, which in some countries cause severe infections in a proportion similar to O157:H7 strains. As several epidemiological studies indicated the important role of meat as the major vehicle in the transmission of this pathogen to human consumers, our aim was to investigate the genetic diversity among non-O157:H7 VTEC isolated from raw beef products. We performed a multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA), and to our knowledge, this is the first time that VTEC serotypes O8:H19, O112:H2, O113:NM, O171:NM, ONT:H7, ONT:H19, and ONT:H21 were typed by this method. MLVA typing grouped the total number of strains from this study (51) into 21 distinct genotypes, and 11 of them were unique. Several MLVA profiles were found in different serotypes, O178:H19 being the most variable. The isolates could be principally discriminated by alleles of three of seven loci studied (CVN001, CVN004, and CVN014), and on the other hand, CVN003 rendered null alleles in all the isolates. As some VNTR markers might be serotype specific, it is possible that the implementation of new VNTR loci will increase intraserotype discrimination.

Multiple-locus variable-nucleotide tandem repeat subtype analysis implicates European starlings as biological vectors for Escherichia coli O157:H7 in Ohio, USA.

PubMed

Williams, M L; Pearl, D L; Lejeune, J T

2011-10-01

To provide molecular epidemiological evidence of avian transmission of Escherichia coli O157:H7 between dairy farms in Ohio, this study was designed to identify genetic relatedness between isolates originating from bovine faecal samples and intestinal contents of European starlings captured on these farms. During a three-year period (2007-2009), cattle (n = 9000) and starlings (n = 430) on 150 different dairy farms in northern Ohio were sampled for the presence of E. coli O157:H7. Isolates were subjected to multiple-locus variable-nucleotide tandem repeat analysis (MLVA). Distinct allelic groups were identified on most farms; however, isolates clustering into three MLVA groups originated from both cattle and birds on different farms. Sharing of indistinguishable epidemiologically linked E. coli O157 MLVA subtypes between starlings and cattle on different farms supports the hypothesis that these birds contribute to the transmission of E. coli O157:H7 between dairy farms. A continued need exists to identify and to improve preharvest measures for controlling E. coli O157:H7. Controlling wildlife intrusion, particularly European starlings, on livestock operations, may be an important strategy for reducing dissemination of E. coli O157:H7 between farms and thereby potentially decreasing the on-farm prevalence of E. coli O157:H7 and enhancing the safety of the food supply. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Seven Salmonella Typhimurium Outbreaks in Australia Linked by Trace-Back and Whole Genome Sequencing.

PubMed

Ford, Laura; Wang, Qinning; Stafford, Russell; Ressler, Kelly-Anne; Norton, Sophie; Shadbolt, Craig; Hope, Kirsty; Franklin, Neil; Krsteski, Radomir; Carswell, Adrienne; Carter, Glen P; Seemann, Torsten; Howard, Peter; Valcanis, Mary; Castillo, Cristina Fabiola Sotomayor; Bates, John; Glass, Kathryn; Williamson, Deborah A; Sintchenko, Vitali; Howden, Benjamin P; Kirk, Martyn D

2018-05-01

Salmonella Typhimurium is a common cause of foodborne illness in Australia. We report on seven outbreaks of Salmonella Typhimurium multilocus variable-number tandem-repeat analysis (MLVA) 03-26-13-08-523 (European convention 2-24-12-7-0212) in three Australian states and territories investigated between November 2015 and March 2016. We identified a common egg grading facility in five of the outbreaks. While no Salmonella Typhimurium was detected at the grading facility and eggs could not be traced back to a particular farm, whole genome sequencing (WGS) of isolates from cases from all seven outbreaks indicated a common source. WGS was able to provide higher discriminatory power than MLVA and will likely link more Salmonella Typhimurium cases between states and territories in the future. National harmonization of Salmonella surveillance is important for effective implementation of WGS for Salmonella outbreak investigations.

Vibrio cholerae O1 El Tor from southern Vietnam in 2010 was molecularly distinct from that present from 1999 to 2004.

PubMed

Nguyen, V H; Pham, H T; Diep, T T; Phan, C D H; Nguyen, T Q; Nguyen, N T N; Ngo, T C; Nguyen, T V; Do, Q K; Phan, H C; Nguyen, B M; Ehara, M; Ohnishi, M; Yamashiro, T; Nguyen, L T P; Izumiya, H

2016-04-01

The Vibrio cholerae O1 (VCO1) El Tor biotype appeared during the seventh cholera pandemic starting in 1961, and new variants of this biotype have been identified since the early 1990s. This pandemic has affected Vietnam, and a large outbreak was reported in southern Vietnam in 2010. Pulsed-field gel electrophoresis (PFGE) and multilocus variable-number tandem-repeat analyses (MLVA) were used to screen 34 VCO1 isolates from the southern Vietnam 2010 outbreak (23 patients, five contact persons, and six environmental isolates) to determine if it was genetically distinct from 18 isolates from outbreaks in southern Vietnam from 1999 to 2004, and two isolates from northern Vietnam (2008). Twenty-seven MLVA types and seven PFGE patterns were identified. Both analyses showed that the 2008 and 2010 isolates were distinctly clustered and separated from the 1999-2004 isolates.

Genetic characterization of Listeria monocytogenes isolates from food processing facilities before and after postcook chiller heat treatment.

PubMed

Eglezos, Sofroni; Dykes, Gary A; Huang, Bixing; Turner, Mark S; Seale, Richard

2013-08-01

Possible selection for and establishment of stress-resistant Listeria monocytogenes variants as a consequence of heating interventions is of concern to the food industry. Lineage analysis and multilocus variable number tandem repeat analysis (MLVA) was performed on 20 L. monocytogenes isolates, of which 15 were obtained before and 5 were obtained after heat treatment of a postcook meat chiller. The ctsR gene (a class III heat shock gene regulator) from 14 isolates was amplified and sequenced because previous work has indicated that spontaneous mutations can occur in this gene during heat treatment. Heat treatment of the meat chiller did not significantly change the relative abundance of the various L. monocytogenes lineages; lineage II strains (less-heat-resistant isolates) dominated both before and after heat treatment. MLVA typing confirmed that some isolates of L. monocytogenes occur both before and after heat treatment of the chiller. No isolate of L. monocytogenes indicated any likely functionally significant mutations in ctsR. This study indicates the absence of any obvious difference in the profiles of L. monocytogenes strains obtained before and after heat treatment of a meat chiller, based on the characteristics examined. Although this finding supports the effectiveness of heat treatment, the limited number of strains used and characteristics examined mean that further study on a larger scale is required before firm conclusions can be drawn.

Genotypic Analyses of Shiga Toxin-Producing Escherichia coli O157 and Non-O157 Recovered from Feces of Domestic Animals on Rural Farms in Mexico

PubMed Central

Amézquita-López, Bianca A.; Quiñones, Beatriz; Cooley, Michael B.; León-Félix, Josefina; Castro-del Campo, Nohelia; Mandrell, Robert E.; Jiménez, Maribel; Chaidez, Cristóbal

2012-01-01

Shiga toxin-producing Escherichia coli (STEC) are zoonotic enteric pathogens associated with human gastroenteritis worldwide. Cattle and small ruminants are important animal reservoirs of STEC. The present study investigated animal reservoirs for STEC in small rural farms in the Culiacan Valley, an important agricultural region located in Northwest Mexico. A total of 240 fecal samples from domestic animals were collected from five sampling sites in the Culiacan Valley and were subjected to an enrichment protocol followed by either direct plating or immunomagnetic separation before plating on selective media. Serotype O157:H7 isolates with the virulence genes stx2, eae, and ehxA were identified in 40% (26/65) of the recovered isolates from cattle, sheep and chicken feces. Pulse-field gel electrophoresis (PFGE) analysis grouped most O157:H7 isolates into two clusters with 98.6% homology. The use of multiple-locus variable-number tandem repeat analysis (MLVA) differentiated isolates that were indistinguishable by PFGE. Analysis of the allelic diversity of MLVA loci suggested that the O157:H7 isolates from this region were highly related. In contrast to O157:H7 isolates, a greater genotypic diversity was observed in the non-O157 isolates, resulting in 23 PFGE types and 14 MLVA types. The relevant non-O157 serotypes O8:H19, O75:H8, O111:H8 and O146:H21 represented 35.4% (23/65) of the recovered isolates. In particular, 18.5% (12/65) of all the isolates were serotype O75:H8, which was the most variable serotype by both PFGE and MLVA. The non-O157 isolates were predominantly recovered from sheep and were identified to harbor either one or two stx genes. Most non-O157 isolates were ehxA-positive (86.5%, 32/37) but only 10.8% (4/37) harbored eae. These findings indicate that zoonotic STEC with genotypes associated with human illness are present in animals on small farms within rural communities in the Culiacan Valley and emphasize the need for the development of control measures to decrease risks associated with zoonotic STEC. PMID:23251577

Genotypic analyses of shiga toxin-producing Escherichia coli O157 and non-O157 recovered from feces of domestic animals on rural farms in Mexico.

PubMed

Amézquita-López, Bianca A; Quiñones, Beatriz; Cooley, Michael B; León-Félix, Josefina; Castro-del Campo, Nohelia; Mandrell, Robert E; Jiménez, Maribel; Chaidez, Cristóbal

2012-01-01

Shiga toxin-producing Escherichia coli (STEC) are zoonotic enteric pathogens associated with human gastroenteritis worldwide. Cattle and small ruminants are important animal reservoirs of STEC. The present study investigated animal reservoirs for STEC in small rural farms in the Culiacan Valley, an important agricultural region located in Northwest Mexico. A total of 240 fecal samples from domestic animals were collected from five sampling sites in the Culiacan Valley and were subjected to an enrichment protocol followed by either direct plating or immunomagnetic separation before plating on selective media. Serotype O157:H7 isolates with the virulence genes stx2, eae, and ehxA were identified in 40% (26/65) of the recovered isolates from cattle, sheep and chicken feces. Pulse-field gel electrophoresis (PFGE) analysis grouped most O157:H7 isolates into two clusters with 98.6% homology. The use of multiple-locus variable-number tandem repeat analysis (MLVA) differentiated isolates that were indistinguishable by PFGE. Analysis of the allelic diversity of MLVA loci suggested that the O157:H7 isolates from this region were highly related. In contrast to O157:H7 isolates, a greater genotypic diversity was observed in the non-O157 isolates, resulting in 23 PFGE types and 14 MLVA types. The relevant non-O157 serotypes O8:H19, O75:H8, O111:H8 and O146:H21 represented 35.4% (23/65) of the recovered isolates. In particular, 18.5% (12/65) of all the isolates were serotype O75:H8, which was the most variable serotype by both PFGE and MLVA. The non-O157 isolates were predominantly recovered from sheep and were identified to harbor either one or two stx genes. Most non-O157 isolates were ehxA-positive (86.5%, 32/37) but only 10.8% (4/37) harbored eae. These findings indicate that zoonotic STEC with genotypes associated with human illness are present in animals on small farms within rural communities in the Culiacan Valley and emphasize the need for the development of control measures to decrease risks associated with zoonotic STEC.

Genetic Relatedness of Staphylococcus haemolyticus in Gut and Skin of Preterm Neonates and Breast Milk of Their Mothers.

PubMed

Soeorg, Hiie; Metsvaht, Hanna Kadri; Keränen, Evamaria Elisabet; Eelmäe, Imbi; Merila, Mirjam; Ilmoja, Mari-Liis; Metsvaht, Tuuli; Lutsar, Irja

2018-04-02

Staphylococcus haemolyticus is a common colonizer and cause of late-onset sepsis (LOS) in preterm neonates. By describing genetic relatedness, we aimed to determine whether mother's breast milk (BM) is a source of S. haemolyticus colonizing neonatal gut and skin and/or causing LOS. S. haemolyticus was isolated from stool and skin swabs of 49 BM-fed preterm neonates admitted to neonatal intensive care unit, 20 healthy BM-fed term neonates and BM of mothers once a week and typed by multilocus variable-number tandem-repeat analysis (MLVA) and multilocus sequence typing (MLST). Virulence-related genes were determined by PCR. Compared with term neonates S. haemolyticus colonized more commonly gut (35% vs 89.9%; p<0.001) and skin (50% vs 91.8%; p<0.001) of preterm neonates and mothers' BM (15% vs 38.8%). Isolates from preterm compared with term neonates and their mothers carried more commonly the mecA gene (83.5% vs 5.4%; p<0.001) and IS256 (52.4% vs 2.7%; p<0.001) and belonged to clonal complex 29 (89.1% vs 63%; p=0.014). Only 7 (14.3%) preterm and 3 (15%) term neonates were colonized in gut or on skin with MLVA-types indistinguishable from those in BM. Most frequent MLVA-types belonged to sequence type 3 or 42, comprised 71.1-78.4% of isolates from preterm neonates/mothers and caused all seven LOS episodes. LOS-causing strain colonized the gut of 4/7 and the skin of 5/7 neonates, but not BM, prior to onset of LOS. S. haemolyticus colonizing gut and skin or causing LOS in preterm neonates rarely originate from BM, but are mecA-positive strains adapted to hospital environment.

Outbreak of Shiga-toxigenic Escherichia coli O157:H7 infections associated with rodeo attendance, Utah and Idaho, 2009.

PubMed

Lanier, William A; Hall, Julia M; Herlihy, Rachel K; Rolfs, Robert T; Wagner, Jennifer M; Smith, Lori H; Hyytia-Trees, Eija K

2011-10-01

In summer 2009, the Utah Department of Health investigated an outbreak of Shiga-toxigenic Escherichia coli (STEC) O157:H7 (O157) illness associated with attendance at multiple rodeos. Patients were interviewed regarding exposures during the week before illness onset. A ground beef traceback investigation was performed. Ground beef samples from patient homes and a grocery store were tested for STEC O157. Rodeo managers were interviewed regarding food vendors present and cattle used at the rodeos. Environmental samples were collected from rodeo grounds. Two-enzyme pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem repeat analysis (MLVA) were performed on isolates. Fourteen patients with primary STEC O157 illness were reported in this outbreak. Isolates from all patients were indistinguishable by PFGE. Isolates from nine patients had identical MLVA patterns (main outbreak strain), and five had minor differences. Thirteen (93%) patients reported ground beef consumption during the week before illness onset. Results of the ground beef traceback investigation and ground beef sampling were negative. Of 12 primary patients asked specifically about rodeo attendance, all reported having attended a rodeo during the week before illness onset; four rodeos were mentioned. All four rodeos had used bulls from the same cattle supplier. An isolate of STEC O157 identified from a dirt sample collected from the bullpens of one of the attended rodeos was indistinguishable by PFGE and MLVA from the main outbreak strain. Recommendations were provided to rodeo management to keep livestock and manure separate from rodeo attendees. This is the first reported STEC O157 outbreak associated with attendance at multiple rodeos. Public health officials should be aware of the potential for rodeo-associated STEC illness.

SNR analysis: molecular investigation of an anthrax epidemic

PubMed Central

2010-01-01

Background In Italy, anthrax is endemic but occurs sporadically. During the summer of 2004, in the Pollino National Park, Basilicata, Southern Italy, an anthrax epidemic consisting of 41 outbreaks occurred; it claimed the lives of 124 animals belonging to different mammal species. This study is a retrospective molecular epidemiological investigation carried out on 53 isolates collected during the epidemic. A 25-loci Multiple Locus VNTR Analysis (MLVA) MLVA was initially performed to define genetic relationships, followed by an investigation of genetic diversity between epidemic strains through Single Nucleotide Repeat (SNR) analysis. Results 53 Bacillus anthracis strains were isolated. The 25-loci MLVA analysis identified all of them as belonging to a single genotype, while the SNR analysis was able to detect the existence of five subgenotypes (SGTs), allowing a detailed epidemic investigation. SGT-1 was the most frequent (46/53); SGTs 2 (4/53), 3 (1/53) 4 (1/53) and 5 (1/53) were detected in the remaining seven isolates. Conclusions The analysis revealed the prevalent spread, during this epidemic, of a single anthrax clone. SGT-1 - widely distributed across the epidemic area and present throughout the period in question - may, thus, be the ancestral form. SGTs 2, 3 and 4 differed from SGT-1 at only one locus, suggesting that they could have evolved directly from the latter during the course of this epidemic. SGT-5 differed from the other SGTs at 2-3 loci. This isolate, thus, appears to be more distantly related to SGT-1 and may not be a direct descendant of the lineage responsible for the majority of cases in this epidemic. These data confirm the importance of molecular typing and subtyping methods for in-depth epidemiological analyses of anthrax epidemics. PMID:20187980

Molecular typing of monophasic Salmonella 4,[5]:i:- strains isolated in Belgium (2008-2011).

PubMed

Boland, Cécile; Bertrand, Sophie; Mattheus, Wesley; Dierick, Katelijne; Wattiau, Pierre

2014-01-31

To assess the distribution of Salmonella 4,[5]:i:- subtypes in the Belgian food chain and compare it to the subtypes associated with human infections, a molecular assessment was initiated. Two hundred fifty-three Salmonella isolates serotyped as 4,[5]:i:- during the period 2008-2011 in Belgium and originating from animal productions, food or human clinical samples were analysed by a specific duplex PCR. One hundred ninety-four isolates (76.7%) fit the profile of a S. Typhimurium monophasic variant as defined by the European Food Safety Authority. The other isolates possessed but did not express the phase II flagellin gene (23.3%). Multiple Locus Variable Number of Tandem Repeats Analysis (MLVA) revealed many but closely related profiles in the fljB-negative S. Typhimurium monophasic variant isolates. Some MLVA types were associated with both human and animal isolates but no unique source of human contamination could be demonstrated. Copyright © 2013 Elsevier B.V. All rights reserved.

Molecular characterization of Mycobacterium tuberculosis isolates from elephants of Nepal.

PubMed

Paudel, Sarad; Mikota, Susan K; Nakajima, Chie; Gairhe, Kamal P; Maharjan, Bhagwan; Thapa, Jeewan; Poudel, Ajay; Shimozuru, Michito; Suzuki, Yasuhiko; Tsubota, Toshio

2014-05-01

Mycobacterium tuberculosis was cultured from the lung tissues of 3 captive elephants in Nepal that died with extensive lung lesions. Spoligotyping, TbD1 detection and multi-locus variable number of tandem repeat analysis (MLVA) results suggested 3 isolates belonged to a specific lineage of Indo-Oceanic clade, EAI5 SIT 138. One of the elephant isolates had a new synonymous single nucleotide polymorphism (SNP) T231C in the gyrA sequence, and the same SNP was also found in human isolates in Nepal. MLVA results and transfer history of the elephants suggested that 2 of them might be infected with M. tuberculosis from the same source. These findings indicated the source of M. tuberculosis infection of those elephants were local residents, presumably their handlers. Further investigation including detailed genotyping of elephant and human isolates is needed to clarify the infection route and eventually prevent the transmission of tuberculosis to susceptible hosts. Copyright © 2014 Elsevier Ltd. All rights reserved.

Molecular typing of Chinese Streptococcus pyogenes isolates.

PubMed

You, Yuanhai; Wang, Haibin; Bi, Zhenwang; Walker, Mark; Peng, Xianhui; Hu, Bin; Zhou, Haijian; Song, Yanyan; Tao, Xiaoxia; Kou, Zengqiang; Meng, Fanliang; Zhang, Menghan; Bi, Zhenqiang; Luo, Fengji; Zhang, Jianzhong

2015-06-01

Streptococcus pyogenes causes human infections ranging from mild pharyngitis and impetigo to serious diseases including necrotizing fasciitis and streptococcal toxic shock syndrome. The objective of this study was to compare molecular emm typing and pulsed field gel electrophoresis (PFGE) with multiple-locus variable-number tandem-repeat analysis (MLVA) for genotyping of Chinese S. pyogenes isolates. Molecular emm typing and PFGE were performed using standard protocols. Seven variable number tandem repeat (VNTR) loci reported in a previous study were used to genotype 169 S. pyogenes geographically-diverse isolates from China isolated from a variety of disease syndromes. Multiple-locus variable-number tandem-repeat analysis provided greater discrimination between isolates when compared to emm typing and PFGE. Removal of a single VNTR locus (Spy2) reduced the sensitivity by only 0.7%, which suggests that Spy2 was not informative for the isolates screened. The results presented support the use of MLVA as a powerful epidemiological tool for genotyping S. pyogenes clinical isolates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Chasing Salmonella Typhimurium in free range egg production system.

PubMed

Chousalkar, Kapil; Gole, Vaibhav; Caraguel, Charles; Rault, Jean-Loup

2016-08-30

Free range production systems are becoming a major source of egg production in Australia and worldwide. This study investigated shedding and ecology of Salmonella Typhimurium and Salmonella species in a free range layer flock, wild birds and foxes in the vicinity of the free range farm in different seasons. Shedding of Salmonella was significantly higher in summer. Within the shed, overall, Salmonella prevalence was highest in dust. Corticosterone level in faeces was highest in spring and lowest in winter. There was no direct association between the Salmonella shedding (MPN/gm) and corticosterone levels in faeces. Salmonella Typhimurium MLVA types isolated from fox and wild birds were similar to MLVA types isolated from layer flock and reported during human food borne illness. Wild birds and foxes appear to play an important role in S. Typhimurium ecology and food safety. Environmental factors could play a role in evolution of S. Typhimurium in free range environment. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Genetic Evolution of Mycobacterium bovis Causing Tuberculosis in Livestock and Wildlife in France since 1978

PubMed Central

Hauer, Amandine; De Cruz, Krystel; Cochard, Thierry; Godreuil, Sylvain; Karoui, Claudine; Henault, Sylvie; Bulach, Tabatha; Bañuls, Anne-Laure; Biet, Franck; Boschiroli, María Laura

2015-01-01

To study the dynamics of bovine tuberculosis (bTB) in France, 4,654 M. bovis strains isolated mainly from livestock and wildlife since 1978 were characterized by spoligotyping and MLVA based on MIRU-VNTR. In our study spoligotyping allowed the discrimination of 176 types although 3 spoligotypes are predominant and account for more than half of the total strain population: SB0120 (26%), SB0134 (11%) and SB0121 (6%). In addition, 11% of the isolates, principally from Southern France, showing close spoligotypes and MIRU-VNTR types have been gathered in a family designated as the “F4-family”. MLVA typing allowed extensive discrimination, particularly for strains with predominant spoligotypes, with a total of 498 genotypes, several of which were highly regionalized. The similarity of the strains’ genetic relationships based on spoligotyping and MIRU-VNTR markers supports the co-existence of different clonal populations within the French M. bovis population. A genetic evolution of the strains was observed both geographically and in time. Indeed, as a result of the reduction of bTB due to the national control campaigns, a large reduction of the strains’ genetic variability took place in the last ten years. However, in the regions were bTB is highly prevalent at present, cases in both livestock and in wildlife are due to the spread of unique local genotype profiles. Our results show that the highly discriminating genotyping tools used in this study for molecular studies of bTB are useful for addressing pending questions, which would lead to a better insight into the epidemiology of the disease, and for finding proper solutions for its sustainable control in France. PMID:25658691

Detection of virulent Escherichia coli O157 strains using multiplex PCR and single base sequencing for SNP characterization.

PubMed

Haugum, K; Brandal, L T; Løbersli, I; Kapperud, G; Lindstedt, B-A

2011-06-01

To compare 167 Norwegian human and nonhuman Escherichia coli O157:H7/NM (nonmotile) isolates with respect to an A/T single nucleotide polymorphism (SNP) in the tir gene and to detect specific SNPs that differentiate STEC O157 into distinct virulence clades (1-3 and 8). We developed a multiplex PCR followed by single base sequencing for detection of the SNPs, and examined the association among SNP genotype, virulence profile (stx and eae status), multilocus variable number of tandem repeats analysis (MLVA) profile and clinical outcome. We found an over-representation of the T allele among human strains compared to nonhuman strains, including 5/6 haemolytic-uraemic syndrome cases. Fourteen strains belonged to clade 8, followed by two clade 2 strains. No clade 1 nor 3 isolates were observed. stx1 in combination with either stx2(EDL933) or stx2c were frequently observed among human strains, whereas stx2c was dominating in nonhuman strains. MLVA indicated that only single cases or small outbreaks with E. coli O157 have been observed in Norway through the years 1993-2008. We observed that the tir-255 A/T SNP and the stx status were different between human and nonhuman O157 strains. No major outbreaks were observed, and only a few strains were differentiated into the virulence clades 2 and 8. The detection of virulence clade-specific SNPs enables the rapid designation of virulent E. coli O157 strains, especially in outbreak situations. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Genetic Characterization and Comparison of Clostridium botulinum Isolates from Botulism Cases in Japan between 2006 and 2011

PubMed Central

Sekizuka, Tsuyoshi; Yamamoto, Akihiko; Iwaki, Masaaki; Komiya, Takako; Hatakeyama, Takashi; Nakajima, Hiroshi; Takahashi, Motohide; Kuroda, Makoto; Shibayama, Keigo

2014-01-01

Genetic characterization was performed for 10 group I Clostridium botulinum strains isolated from botulism cases in Japan between 2006 and 2011. Of these, 1 was type A, 2 were type B, and 7 were type A(B) {carrying a silent bont/B [bont/(B)] gene} serotype strains, based on botulinum neurotoxin (BoNT) production. The type A strain harbored the subtype A1 BoNT gene (bont/A1), which is associated with the ha gene cluster. The type B strains carried bont/B5 or bont/B6 subtype genes. The type A(B) strains carried bont/A1 identical to that of type A(B) strain NCTC2916. However, bont/(B) genes in these strains showed single-nucleotide polymorphisms (SNPs) among strains. SNPs at 2 nucleotide positions of bont/(B) enabled classification of the type A(B) strains into 3 groups. Pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem-repeat analysis (MLVA) also provided consistent separation results. In addition, the type A(B) strains were separated into 2 lineages based on their plasmid profiles. One lineage carried a small plasmid (5.9 kb), and another harbored 21-kb plasmids. To obtain more detailed genetic information about the 10 strains, we sequenced their genomes and compared them with 13 group I C. botulinum genomes in a database using whole-genome SNP analysis. This analysis provided high-resolution strain discrimination and enabled us to generate a refined phylogenetic tree that provides effective traceability of botulism cases, as well as bioterrorism materials. In the phylogenetic tree, the subtype B6 strains, Okayama2011 and Osaka05, were distantly separated from the other strains, indicating genomic divergence of subtype B6 strains among group I strains. PMID:25192986

Cases of human brucellosis in Sweden linked to Middle East and Africa.

PubMed

Garofolo, Giuliano; Fasanella, Antonio; Di Giannatale, Elisabetta; Platone, Ilenia; Sacchini, Lorena; Persiani, Tiziana; Boskani, Talar; Rizzardi, Kristina; Wahab, Tara

2016-05-17

Human brucellosis cases are still reported each year in Sweden despite eradication of the disease in animals. Epidemiological investigation has never been conducted to trace back the source of human infection in the country. The purpose of the study was to identify the source of infection for 16 human brucellosis cases that occurred in Sweden, during the period 2008-2012. The isolates were identified as Brucella melitensis and MLVA-16 genotyping revealed 14 different genotypes of East Mediterranean and Africa lineages. We also reported one case of laboratory-acquired brucellosis (LAB) that was shown to be epidemiological linked to one of the cases in the current study. Brucella melitensis was the only species diagnosed, confirming its highest zoonotic potential in the genus Brucella, and MLVA-16 results demonstrated that the cases of brucellosis in Sweden herein investigated, are imported and linked to travel in the Middle East and Africa. Due to its zoonotic concerns, any acute febrile illness linked to recent travel within those regions should be investigated for brucellosis and samples should be processed according to biosafety level 3 regulations.

Molecular epidemiological investigation of Brucella melitensis circulating in Mongolia by MLVA16.

PubMed

Kang, Sung-Il; Her, Moon; Erdenebaataar, Janchivdorj; Vanaabaatar, Batbaatar; Cho, Hyorim; Sung, So-Ra; Lee, Jin Ju; Jung, Suk Chan; Park, Yong Ho; Kim, Ji-Yeon

2017-02-01

Mongolia has a high incidence of brucellosis in human and animals due to livestock husbandry. To investigate the genetic characteristics of Mongolian B. melitensis, an MLVA (multi-locus variable-number tandem-repeat analysis)-16 assay was performed with 94 B. melitensis isolates. They were identified as B. melitensis biovar (bv.) 1 (67), 3 (10) and Rev. 1 vaccine strains (17) using a classical biotyping and multiplex PCR. In genotyping, three human isolates were grouped at 2 genotypes with sheep isolates, and it implies that B. melitensis are cross-infected between human and livestock. In the parsimony analysis, Mongolian B. melitensis isolates had high genetic similarity with Chinese strains, likely due to the geographical proximity, clustered distinctively as compared with other foreign isolates. B. melitensis Rev. 1 vaccine strains were divided into 4 genotypes with 92% similarity. In the analysis of Rev.1 strains, the risk of mutation of vaccine strain might not be overlooked. Animal quarantines should be strengthened to prevent the spread of Brucella species among adjacent countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of Genotypes of Salmonella enterica Serovar Enteritidis Phage Type 30 and 9c Strains Isolated during Three Outbreaks Associated with Raw Almonds▿

PubMed Central

Parker, Craig T.; Huynh, Steven; Quiñones, Beatriz; Harris, Linda J.; Mandrell, Robert E.

2010-01-01

In 2000 to 2001, 2003 to 2004, and 2005 to 2006, three outbreaks of Salmonella enterica serovar Enteritidis were linked with the consumption of raw almonds. The S. Enteritidis strains from these outbreaks had rare phage types (PT), PT30 and PT9c. Clinical and environmental S. Enteritidis strains were subjected to pulsed-field gel electrophoresis (PFGE), multilocus variable-number tandem repeat analysis (MLVA), and DNA microarray-based comparative genomic indexing (CGI) to evaluate their genetic relatedness. All three methods differentiated these S. Enteritidis strains in a manner that correlated with PT. The CGI analysis confirmed that the majority of the differences between the S. Enteritidis PT9c and PT30 strains corresponded to bacteriophage-related genes present in the sequenced genomes of S. Enteritidis PT4 and S. enterica serovar Typhimurium LT2. However, PFGE, MLVA, and CGI failed to discriminate between S. Enteritidis PT30 strains related to outbreaks from unrelated clinical strains or between strains separated by up to 5 years. However, metabolic fingerprinting demonstrated that S. Enteritidis PT4, PT8, PT13a, and clinical PT30 strains metabolized l-aspartic acid, l-glutamic acid, l-proline, l-alanine, and d-alanine amino acids more efficiently than S. Enteritidis PT30 strains isolated from orchards. These data indicate that S. Enteritidis PT9c and 30 strains are highly related genetically and that PT30 orchard strains differ from clinical PT30 strains metabolically, possibly due to fitness adaptations. PMID:20363782

Isolation and molecular characterization of Leptospira borgpetersenii serovar Hardjo strain Hardjobovis in the urine of naturally infected cattle in Brazil.

PubMed

Chideroli, R T; Pereira, U P; Gonçalves, D D; Nakamura, A Y; Alfieri, A A; Alfieri, A F; Freitas, J C

2016-02-19

Most epidemiologic studies on bovine leptospirosis are based on serological tests that use antibodies against several serotypes, including the serovar Hardjo, which is widespread and considered to be the most adapted to bovine hosts. However, using only serological studies is not sufficient to identify and distinguish species of leptospires. The aim of this study was report the first isolation in Brazil of two strains serovar Hardjo obtained in urine samples from naturally infected cows in a small Brazilian dairy herd and find the genetic species and consequently the type strain Hardjobovis by molecular characterization. Fifteen dairy cows with a history of reproductive failure, such as abortion and infertility, were selected. Urine samples obtained from each animal were immediately seeded in tubes containing Ellinghausen-McCullough-Johnson-Harris culture medium. The identification of the isolates was performed by Multilocus variable-number tandem-repeat analysis (MLVA) technique and phylogenetic analysis of partial sequence of gene sec Y. From the 15 urine samples evaluated, two Leptospira were found and identified as the Londrina 49 and Londrina 54 strains. The MLVA profiles and sequencing of gene sec Y characterized the isolates as L. borgpetersenii serovar Hardjo strain Hadjobovis because it has different genetic pattern of Leptospira interrogans serovar Hardjo strain Hardjoprajitno. Therefore, more studies are needed including isolation and molecular characterization from regional strains to obtain a better knowledge about epidemiology of serovar Hardjo in bovine which may assist in future strategies of prevention and control of bovine leptospirosis.

Outbreak of haemolytic uraemic syndrome in Norway caused by stx2-positive Escherichia coli O103:H25 traced to cured mutton sausages

PubMed Central

Schimmer, Barbara; Nygard, Karin; Eriksen, Hanne-Merete; Lassen, Jørgen; Lindstedt, Bjørn-Arne; Brandal, Lin T; Kapperud, Georg; Aavitsland, Preben

2008-01-01

Background On 20–21 February 2006, six cases of diarrhoea-associated haemolytic uraemic syndrome (HUS) were reported by paediatricians to the Norwegian Institute of Public Health. We initiated an investigation to identify the etiologic agent and determine the source of the outbreak in order to implement control measures. Methods A case was defined as a child with diarrhoea-associated HUS or any person with an infection with the outbreak strain of E. coli O103 (defined by the multi-locus variable number tandem repeats analysis (MLVA) profile) both with illness onset after January 1st 2006 in Norway. After initial hypotheses-generating interviews, we performed a case-control study with the first fifteen cases and three controls for each case matched by age, sex and municipality. Suspected food items were sampled, and any E. coli O103 strains were typed by MLVA. Results Between 20 February and 6 April 2006, 17 cases were identified, of which 10 children developed HUS, including one fatal case. After pilot interviews, a matched case-control study was performed indicating an association between a traditional cured sausage (odds ratio 19.4 (95% CI: 2.4–156)) and STEC infection. E. coli O103:H25 identical to the outbreak strain defined by MLVA profile was found in the product and traced back to contaminated mutton. Conclusion We report an outbreak caused by a rare STEC variant (O103:H25, stx2-positive). More than half of the diagnosed patients developed HUS, indicating that the causative organism is particularly virulent. Small ruminants continue to be important reservoirs for human-pathogen STEC. Improved slaughtering hygiene and good manufacturing practices for cured sausage products are needed to minimise the possibility of STEC surviving through the entire sausage production process. PMID:18387178

Genetic Variation of Bordetella pertussis in Austria.

PubMed

Wagner, Birgit; Melzer, Helen; Freymüller, Georg; Stumvoll, Sabine; Rendi-Wagner, Pamela; Paulke-Korinek, Maria; Repa, Andreas; Mooi, Frits R; Kollaritsch, Herwig; Mittermayer, Helmut; Kessler, Harald H; Stanek, Gerold; Steinborn, Ralf; Duchêne, Michael; Wiedermann, Ursula

2015-01-01

In Austria, vaccination coverage against Bordetella pertussis infections during infancy is estimated at around 90%. Within the last years, however, the number of pertussis cases has increased steadily, not only in children but also in adolescents and adults, indicating both insufficient herd immunity and vaccine coverage. Waning immunity in the host and/or adaptation of the bacterium to the immunised hosts could contribute to the observed re-emergence of pertussis. In this study we therefore addressed the genetic variability in B. pertussis strains from several Austrian cities. Between the years 2002 and 2008, 110 samples were collected from Vienna (n = 32), Linz (n = 63) and Graz (n = 15) by nasopharyngeal swabs. DNA was extracted from the swabs, and bacterial sequence polymorphisms were examined by MLVA (multiple-locus variable number of tandem repeat analysis) (n = 77), by PCR amplification and conventional Sanger sequencing of the polymorphic regions of the prn (pertactin) gene (n = 110), and by amplification refractory mutation system quantitative PCR (ARMS-qPCR) (n = 110) to directly address polymorphisms in the genes encoding two pertussis toxin subunits (ptxA and ptxB), a fimbrial adhesin (fimD), tracheal colonisation factor (tcfA), and the virulence sensor protein (bvgS). Finally, the ptxP promoter region was screened by ARMS-qPCR for the presence of the ptxP3 allele, which has been associated with elevated production of pertussis toxin. The MLVA analysis revealed the highest level of polymorphisms with an absence of MLVA Type 29, which is found outside Austria. Only Prn subtypes Prn1/7, Prn2 and Prn3 were found with a predominance of the non-vaccine type Prn2. The analysis of the ptxA, ptxB, fimD, tcfA and bvgS polymorphisms showed a genotype mixed between the vaccine strain Tohama I and a clinical isolate from 2006 (L517). The major part of the samples (93%) displayed the ptxP3 allele. The consequences for the vaccination strategy are discussed.

Dynamics of Salmonella Shedding and Welfare of Hens in Free-Range Egg Production Systems

PubMed Central

Gole, Vaibhav C.; Woodhouse, Rebecca; Caraguel, Charles; Moyle, Talia; Rault, Jean-Loup; Sexton, Margaret

2016-01-01

ABSTRACT The current study investigated the effect of environmental stressors (i.e., weather changes) on Salmonella shedding in free-range production systems and the correlations with behavioral and physiological measures (i.e., fecal glucocorticoid metabolites). This involved longitudinal and point-in-time surveys of Salmonella shedding and environmental contamination on four commercial free-range layer farms. The shedding of Salmonella was variable across free-range farms and in different seasons. There was no significant effect of season on the Salmonella prevalence during this investigation. In this study, the combined Salmonella most probable number (MPN) counts in environmental (including feces, egg belt, dust, nest box, and ramp) samples were highest in samples collected during the summer season (4th sampling, performed in February). The predominant serovars isolated during this study were Salmonella enterica serovar Mbandaka and Salmonella enterica serovar Typhimurium phage types 135 and 135a. These two phage types were involved in several egg product-related Salmonella outbreaks in humans. Multilocus variable-number tandem-repeat analysis (MLVA) results indicated that MLVA types detected from human food poisoning cases exhibited MLVA patterns similar to the strains isolated during this study. All Salmonella isolates (n = 209) were tested for 15 different genes involved in adhesion, invasion, and survival of Salmonella spp. We also observed variations for sopA, ironA, and misL. There were no positive correlations between fecal corticosterone metabolite (FCM) and Salmonella prevalence and/or shedding in feces. Also, there were no positive correlations between Salmonella prevalence and Salmonella count (log MPN) and any of the other welfare parameters. IMPORTANCE In this study, the welfare of laying hens and Salmonella shedding were compared over a prolonged period of time in field conditions. This study investigated the long-term shedding of Salmonella serovars in a free-range egg production system. Given that there is increasing demand for free-range eggs, it is essential to understand the risks associated with such a production system. PMID:28039133

Dynamics of Salmonella Shedding and Welfare of Hens in Free-Range Egg Production Systems.

PubMed

Gole, Vaibhav C; Woodhouse, Rebecca; Caraguel, Charles; Moyle, Talia; Rault, Jean-Loup; Sexton, Margaret; Chousalkar, Kapil

2017-03-01

The current study investigated the effect of environmental stressors (i.e., weather changes) on Salmonella shedding in free-range production systems and the correlations with behavioral and physiological measures (i.e., fecal glucocorticoid metabolites). This involved longitudinal and point-in-time surveys of Salmonella shedding and environmental contamination on four commercial free-range layer farms. The shedding of Salmonella was variable across free-range farms and in different seasons. There was no significant effect of season on the Salmonella prevalence during this investigation. In this study, the combined Salmonella most probable number (MPN) counts in environmental (including feces, egg belt, dust, nest box, and ramp) samples were highest in samples collected during the summer season (4th sampling, performed in February). The predominant serovars isolated during this study were Salmonella enterica serovar Mbandaka and Salmonella enterica serovar Typhimurium phage types 135 and 135a. These two phage types were involved in several egg product-related Salmonella outbreaks in humans. Multilocus variable-number tandem-repeat analysis (MLVA) results indicated that MLVA types detected from human food poisoning cases exhibited MLVA patterns similar to the strains isolated during this study. All Salmonella isolates ( n = 209) were tested for 15 different genes involved in adhesion, invasion, and survival of Salmonella spp. We also observed variations for sopA , ironA , and misL There were no positive correlations between fecal corticosterone metabolite (FCM) and Salmonella prevalence and/or shedding in feces. Also, there were no positive correlations between Salmonella prevalence and Salmonella count (log MPN) and any of the other welfare parameters. IMPORTANCE In this study, the welfare of laying hens and Salmonella shedding were compared over a prolonged period of time in field conditions. This study investigated the long-term shedding of Salmonella serovars in a free-range egg production system. Given that there is increasing demand for free-range eggs, it is essential to understand the risks associated with such a production system. Copyright © 2017 American Society for Microbiology.

Multiple-locus variable-number tandem repeat analysis for molecular typing of Aspergillus fumigatus

PubMed Central

2010-01-01

Background Multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA) is a prominent subtyping method to resolve closely related microbial isolates to provide information for establishing genetic patterns among isolates and to investigate disease outbreaks. The usefulness of MLVA was recently demonstrated for the avian major pathogen Chlamydophila psittaci. In the present study, we developed a similar method for another pathogen of birds: the filamentous fungus Aspergillus fumigatus. Results We selected 10 VNTR markers located on 4 different chromosomes (1, 5, 6 and 8) of A. fumigatus. These markers were tested with 57 unrelated isolates from different hosts or their environment (53 isolates from avian species in France, China or Morocco, 3 isolates from humans collected at CHU Henri Mondor hospital in France and the reference strain CBS 144.89). The Simpson index for individual markers ranged from 0.5771 to 0.8530. A combined loci index calculated with all the markers yielded an index of 0.9994. In a second step, the panel of 10 markers was used in different epidemiological situations and tested on 277 isolates, including 62 isolates from birds in Guangxi province in China, 95 isolates collected in two duck farms in France and 120 environmental isolates from a turkey hatchery in France. A database was created with the results of the present study http://minisatellites.u-psud.fr/MLVAnet/. Three major clusters of isolates were defined by using the graphing algorithm termed Minimum Spanning Tree (MST). The first cluster comprised most of the avian isolates collected in the two duck farms in France, the second cluster comprised most of the avian isolates collected in poultry farms in China and the third one comprised most of the isolates collected in the turkey hatchery in France. Conclusions MLVA displayed excellent discriminatory power. The method showed a good reproducibility. MST analysis revealed an interesting clustering with a clear separation between isolates according to their geographic origin rather than their respective hosts. PMID:21143842

Mycobacterium avium subsp. hominissuis infection in swine associated with peat used for bedding.

PubMed

Johansen, Tone Bjordal; Agdestein, Angelika; Lium, Bjørn; Jørgensen, Anne; Djønne, Berit

2014-01-01

Mycobacterium avium subsp. hominissuis is an environmental bacterium causing opportunistic infections in swine, resulting in economic losses. Additionally, the zoonotic aspect of such infections is of concern. In the southeastern region of Norway in 2009 and 2010, an increase in condemnation of pig carcasses with tuberculous lesions was seen at the meat inspection. The use of peat as bedding in the herds was suspected to be a common factor, and a project examining pigs and environmental samples from the herds was initiated. Lesions detected at meat inspection in pigs originating from 15 herds were sampled. Environmental samples including peat from six of the herds and from three peat production facilities were additionally collected. Samples were analysed by culture and isolates genotyped by MLVA analysis. Mycobacterium avium subsp. hominissuis was detected in 35 out of 46 pigs, in 16 out of 20 samples of peat, and in one sample of sawdust. MLVA analysis demonstrated identical isolates from peat and pigs within the same farms. Polyclonal infection was demonstrated by analysis of multiple isolates from the same pig. To conclude, the increase in condemnation of porcine carcasses at slaughter due to mycobacteriosis seemed to be related to untreated peat used as bedding.

Mycobacterium avium subsp. hominissuis Infection in Swine Associated with Peat Used for Bedding

PubMed Central

Johansen, Tone Bjordal; Lium, Bjørn; Jørgensen, Anne; Djønne, Berit

2014-01-01

Mycobacterium avium subsp. hominissuis is an environmental bacterium causing opportunistic infections in swine, resulting in economic losses. Additionally, the zoonotic aspect of such infections is of concern. In the southeastern region of Norway in 2009 and 2010, an increase in condemnation of pig carcasses with tuberculous lesions was seen at the meat inspection. The use of peat as bedding in the herds was suspected to be a common factor, and a project examining pigs and environmental samples from the herds was initiated. Lesions detected at meat inspection in pigs originating from 15 herds were sampled. Environmental samples including peat from six of the herds and from three peat production facilities were additionally collected. Samples were analysed by culture and isolates genotyped by MLVA analysis. Mycobacterium avium subsp. hominissuis was detected in 35 out of 46 pigs, in 16 out of 20 samples of peat, and in one sample of sawdust. MLVA analysis demonstrated identical isolates from peat and pigs within the same farms. Polyclonal infection was demonstrated by analysis of multiple isolates from the same pig. To conclude, the increase in condemnation of porcine carcasses at slaughter due to mycobacteriosis seemed to be related to untreated peat used as bedding. PMID:25431762

Ruminant Rhombencephalitis-Associated Listeria monocytogenes Alleles Linked to a Multilocus Variable-Number Tandem-Repeat Analysis Complex ▿ †

PubMed Central

Balandyté, Lina; Brodard, Isabelle; Frey, Joachim; Oevermann, Anna; Abril, Carlos

2011-01-01

Listeria monocytogenes is among the most important food-borne pathogens and is well adapted to persist in the environment. To gain insight into the genetic relatedness and potential virulence of L. monocytogenes strains causing central nervous system (CNS) infections, we used multilocus variable-number tandem-repeat analysis (MLVA) to subtype 183 L. monocytogenes isolates, most from ruminant rhombencephalitis and some from human patients, food, and the environment. Allelic-profile-based comparisons grouped L. monocytogenes strains mainly into three clonal complexes and linked single-locus variants (SLVs). Clonal complex A essentially consisted of isolates from human and ruminant brain samples. All but one rhombencephalitis isolate from cattle were located in clonal complex A. In contrast, food and environmental isolates mainly clustered into clonal complex C, and none was classified as clonal complex A. Isolates of the two main clonal complexes (A and C) obtained by MLVA were analyzed by PCR for the presence of 11 virulence-associated genes (prfA, actA, inlA, inlB, inlC, inlD, inlE, inlF, inlG, inlJ, and inlC2H). Virulence gene analysis revealed significant differences in the actA, inlF, inlG, and inlJ allelic profiles between clinical isolates (complex A) and nonclinical isolates (complex C). The association of particular alleles of actA, inlF, and newly described alleles of inlJ with isolates from CNS infections (particularly rhombencephalitis) suggests that these virulence genes participate in neurovirulence of L. monocytogenes. The overall absence of inlG in clinical complex A and its presence in complex C isolates suggests that the InlG protein is more relevant for the survival of L. monocytogenes in the environment. PMID:21984240

Molecular Typing and Virulence Gene Profiles of Enterotoxin Gene Cluster (egc)-Positive Staphylococcus aureus Isolates Obtained from Various Food and Clinical Specimens.

PubMed

Song, Minghui; Shi, Chunlei; Xu, Xuebing; Shi, Xianming

2016-11-01

The enterotoxin gene cluster (egc) has been proposed to contribute to the Staphylococcus aureus colonization, which highlights the need to evaluate genetic diversity and virulence gene profiles of the egc-positive population. Here, a total of 43 egc-positive isolates (16.2%) were identified from 266 S. aureus isolates that were obtained from various food and clinical specimens in Shanghai. Seven different egc profiles were found based on the polymerase chain reaction (PCR) result for egc genes. Then, these 43 egc-positive isolates were further typed by multilocus sequence typing, pulsed-field gel electrophoresis (PFGE), multiple-locus variable-number tandem-repeat analysis (MLVA), and accessory gene regulatory (agr) typing. It showed that the 43 egc-positive isolates displayed 17 sequence types, 28 PFGE patterns, 29 MLVA types, and 4 agr types, respectively. Among them, the dominant clonal lineage was CC5-agr II (48.84%). Thirty toxin and 20 adhesion-associated genes were detected by PCR in egc-positive isolates. Notably, invasive toxin genes showed a high prevalence, such as 76.7% for Panton-Valentine leukocidin encoding genes, 27.9% for sec, and 23.3% for tsst-1. Most of the examined adhesion-associated genes were found to be conserved (76.7-100%), whereas the fnbB gene was only found in 8 (18.6%) isolates. In addition, 33 toxin gene profiles and 13 adhesion gene profiles were identified, respectively. Our results imply that isolates belonging to the same clonal lineage harbored similar adhesion gene profiles but diverse toxin gene profiles. Overall, the high prevalence of invasive virulence genes increases the potential risk of egc-positive isolates in S. aureus infection.

Utility of Whole-Genome Sequencing of Escherichia coli O157 for Outbreak Detection and Epidemiological Surveillance.

PubMed

Holmes, Anne; Allison, Lesley; Ward, Melissa; Dallman, Timothy J; Clark, Richard; Fawkes, Angie; Murphy, Lee; Hanson, Mary

2015-11-01

Detailed laboratory characterization of Escherichia coli O157 is essential to inform epidemiological investigations. This study assessed the utility of whole-genome sequencing (WGS) for outbreak detection and epidemiological surveillance of E. coli O157, and the data were used to identify discernible associations between genotypes and clinical outcomes. One hundred five E. coli O157 strains isolated over a 5-year period from human fecal samples in Lothian, Scotland, were sequenced with the Ion Torrent Personal Genome Machine. A total of 8,721 variable sites in the core genome were identified among the 105 isolates; 47% of the single nucleotide polymorphisms (SNPs) were attributable to six "atypical" E. coli O157 strains and included recombinant regions. Phylogenetic analyses showed that WGS correlated well with the epidemiological data. Epidemiological links existed between cases whose isolates differed by three or fewer SNPs. WGS also correlated well with multilocus variable-number tandem repeat analysis (MLVA) typing data, with only three discordant results observed, all among isolates from cases not known to be epidemiologically related. WGS produced a better-supported, higher-resolution phylogeny than MLVA, confirming that the method is more suitable for epidemiological surveillance of E. coli O157. A combination of in silico analyses (VirulenceFinder, ResFinder, and local BLAST searches) were used to determine stx subtypes, multilocus sequence types (15 loci), and the presence of virulence and acquired antimicrobial resistance genes. There was a high level of correlation between the WGS data and our routine typing methods, although some discordant results were observed, mostly related to the limitation of short sequence read assembly. The data were used to identify sublineages and clades of E. coli O157, and when they were correlated with the clinical outcome data, they showed that one clade, Ic3, was significantly associated with severe disease. Together, the results show that WGS data can provide higher resolution of the relationships between E. coli O157 isolates than that provided by MLVA. The method has the potential to streamline the laboratory workflow and provide detailed information for the clinical management of patients and public health interventions. Copyright © 2015, Holmes et al.

Utility of Whole-Genome Sequencing of Escherichia coli O157 for Outbreak Detection and Epidemiological Surveillance

PubMed Central

Allison, Lesley; Ward, Melissa; Dallman, Timothy J.; Clark, Richard; Fawkes, Angie; Murphy, Lee; Hanson, Mary

2015-01-01

Detailed laboratory characterization of Escherichia coli O157 is essential to inform epidemiological investigations. This study assessed the utility of whole-genome sequencing (WGS) for outbreak detection and epidemiological surveillance of E. coli O157, and the data were used to identify discernible associations between genotypes and clinical outcomes. One hundred five E. coli O157 strains isolated over a 5-year period from human fecal samples in Lothian, Scotland, were sequenced with the Ion Torrent Personal Genome Machine. A total of 8,721 variable sites in the core genome were identified among the 105 isolates; 47% of the single nucleotide polymorphisms (SNPs) were attributable to six “atypical” E. coli O157 strains and included recombinant regions. Phylogenetic analyses showed that WGS correlated well with the epidemiological data. Epidemiological links existed between cases whose isolates differed by three or fewer SNPs. WGS also correlated well with multilocus variable-number tandem repeat analysis (MLVA) typing data, with only three discordant results observed, all among isolates from cases not known to be epidemiologically related. WGS produced a better-supported, higher-resolution phylogeny than MLVA, confirming that the method is more suitable for epidemiological surveillance of E. coli O157. A combination of in silico analyses (VirulenceFinder, ResFinder, and local BLAST searches) were used to determine stx subtypes, multilocus sequence types (15 loci), and the presence of virulence and acquired antimicrobial resistance genes. There was a high level of correlation between the WGS data and our routine typing methods, although some discordant results were observed, mostly related to the limitation of short sequence read assembly. The data were used to identify sublineages and clades of E. coli O157, and when they were correlated with the clinical outcome data, they showed that one clade, Ic3, was significantly associated with severe disease. Together, the results show that WGS data can provide higher resolution of the relationships between E. coli O157 isolates than that provided by MLVA. The method has the potential to streamline the laboratory workflow and provide detailed information for the clinical management of patients and public health interventions. PMID:26354815

Virulence Factors of Streptococcus pneumoniae. Comparison between African and French Invasive Isolates and Implication for Future Vaccines.

PubMed

Blumental, Sophie; Granger-Farbos, Alexandra; Moïsi, Jennifer C; Soullié, Bruno; Leroy, Philippe; Njanpop-Lafourcade, Berthe-Marie; Yaro, Seydou; Nacro, Boubacar; Hallin, Marie; Koeck, Jean-Louis

2015-01-01

Many surface proteins thought to promote Streptocococcus pneumoniae virulence have recently been discovered and are currently being considered as future vaccine targets. We assessed the prevalence of 16 virulence genes among 435 S. pneumoniae invasive isolates from France and the "African meningitis belt" region, with particular focus on serotype 1 (Sp1), to compare their geographical distribution, assess their association with site of infection and evaluate their potential interest as new vaccine candidates. Detection by PCR of pspA (+families), pspC (+pspC.4), pavA, lytA, phtA,B,D,E, nanA,B,C, rrgA (Pilus-1), sipA (Pilus-2), pcpA and psrp was performed on all isolates, as well as antibiotic resistance testing and MLVA typing (+MLST on 54 representative strains). Determination of ply alleles was performed by sequencing (Sp1 isolates). MLVA and virulence genes profiles segregated Sp1 isolates into 2 groups that followed continent distribution. The ply allele 5 and most of the genes that were variable (nanC, Pilus-2, psrp, pcpA, phtD) were present in the French Sp1 isolates (PMEN clone Sweden(1)-28, ST306) but absent from the African ones. Whereas all African Sp1 isolates clustered into a single MLST CC (CC217), MLVA distinguished two CCs that followed temporal evolution. Pilus-2 and psrp were more prevalent in bacteraemic pneumonia yielded isolates and phtB in meningitis-related isolates. Considering vaccine candidates, phtD was less prevalent than anticipated (50%) and pcpA varied importantly between France and Africa (98% versus 34%). Pilus-1 was carried by 7-11% of isolates and associated with β-lactams resistance. Most virulence genes were carried by the European ST306 clone but were lacking on Sp1 isolates circulating in the African meningitis belt, where a more serious pattern of infection is observed. While virulence proteins are now considered as vaccine targets, the geographical differences in their prevalence could affect the efficacy expected from future vaccines.

Virulence Factors of Streptococcus pneumoniae. Comparison between African and French Invasive Isolates and Implication for Future Vaccines

PubMed Central

Blumental, Sophie; Granger-Farbos, Alexandra; Moïsi, Jennifer C.; Soullié, Bruno; Leroy, Philippe; Njanpop-Lafourcade, Berthe-Marie; Yaro, Seydou; Nacro, Boubacar; Hallin, Marie; Koeck, Jean-Louis

2015-01-01

Background Many surface proteins thought to promote Streptocococcus pneumoniae virulence have recently been discovered and are currently being considered as future vaccine targets. We assessed the prevalence of 16 virulence genes among 435 S. pneumoniae invasive isolates from France and the “African meningitis belt” region, with particular focus on serotype 1 (Sp1), to compare their geographical distribution, assess their association with site of infection and evaluate their potential interest as new vaccine candidates. Methods Detection by PCR of pspA (+families), pspC (+pspC.4), pavA, lytA, phtA,B,D,E, nanA,B,C, rrgA (Pilus-1), sipA (Pilus-2), pcpA and psrp was performed on all isolates, as well as antibiotic resistance testing and MLVA typing (+MLST on 54 representative strains). Determination of ply alleles was performed by sequencing (Sp1 isolates). Results MLVA and virulence genes profiles segregated Sp1 isolates into 2 groups that followed continent distribution. The ply allele 5 and most of the genes that were variable (nanC, Pilus-2, psrp, pcpA, phtD) were present in the French Sp1 isolates (PMEN clone Sweden1-28, ST306) but absent from the African ones. Whereas all African Sp1 isolates clustered into a single MLST CC (CC217), MLVA distinguished two CCs that followed temporal evolution. Pilus-2 and psrp were more prevalent in bacteraemic pneumonia yielded isolates and phtB in meningitis-related isolates. Considering vaccine candidates, phtD was less prevalent than anticipated (50%) and pcpA varied importantly between France and Africa (98% versus 34%). Pilus-1 was carried by 7-11% of isolates and associated with β-lactams resistance. Conclusions Most virulence genes were carried by the European ST306 clone but were lacking on Sp1 isolates circulating in the African meningitis belt, where a more serious pattern of infection is observed. While virulence proteins are now considered as vaccine targets, the geographical differences in their prevalence could affect the efficacy expected from future vaccines. PMID:26214695

Genetically Similar Isolates of Salmonella enterica Serotype Enteritidis Persistent in China for a Long-Term Period.

PubMed

Song, Qifa; Shen, Xuanyi; Yang, Yuanbin; Zhang, Danyang; Gao, Hong

2016-07-01

Salmonella enterica serotype Enteritidis (S. Enteritidis) is an important causative agent of nontyphoidal salmonellosis in human populations. In this study, we collected 72 S. Enteritidis strains from 2004 to 2014 in Ningbo, mid-east China. Of the 72 strains, we identified a dominant clone of 58 strains recovered from patient's feces (n = 48), blood (n = 1), pleural effusion (n = 1), chickens (n = 3), and dessert cakes (n = 5) by pulsed-field gel electrophoresis (PFGE) and variable-number of tandem repeat analysis (MLVA). The profile arrangements of MLVA were SE1-SE2-SE3-SE5-SE6-SE8-SE9: 4-4-3-11-10-1-3. These dominant strains were susceptible to ampicillin, chloramphenicol, tetracycline, ciprofloxacin, gentamicin, cefotaxime and trimethoprim-sulfamethoxazole, and resistant to nalidixic acid. Additionally, all isolates harboured virulence genes invA, sipA, sopE, and spvB when tested by PCR. Our results reveal that genetically similar S. Enteritidis strains which accounted for several outbreaks as well as blood infection and pleural cavity infection are prevalent in China for a long-term period. This situation calls for further attention in the prevention and control of foodborne disease caused by Salmonella species. © 2016 Institute of Food Technologists®

Assessment of genetic diversity of zoonotic Brucella spp. recovered from livestock in Egypt using multiple locus VNTR analysis.

PubMed

Menshawy, Ahmed M S; Perez-Sancho, Marta; Garcia-Seco, Teresa; Hosein, Hosein I; García, Nerea; Martinez, Irene; Sayour, Ashraf E; Goyache, Joaquín; Azzam, Ragab A A; Dominguez, Lucas; Alvarez, Julio

2014-01-01

Brucellosis is endemic in most parts of Egypt, where it is caused mainly by Brucella melitensis biovar 3, and affects cattle and small ruminants in spite of ongoing efforts devoted to its control. Knowledge of the predominant Brucella species/strains circulating in a region is a prerequisite of a brucellosis control strategy. For this reason a study aiming at the evaluation of the phenotypic and genetic heterogeneity of a panel of 17 Brucella spp. isolates recovered from domestic ruminants (cattle, buffalo, sheep, and goat) from four governorates during a period of five years (2002-2007) was carried out using microbiological tests and molecular biology techniques (PCR, MLVA-15, and sequencing). Thirteen strains were identified as B. melitensis biovar 3 while all phenotypic and genetic techniques classified the remaining isolates as B. abortus (n = 2) and B. suis biovar 1 (n = 2). MLVA-15 yielded a high discriminatory power (h = 0.801), indicating a high genetic diversity among the B. melitensis strains circulating among domestic ruminants in Egypt. This is the first report of the isolation of B. suis from cattle in Egypt which, coupled with the finding of B. abortus, suggests a potential role of livestock as reservoirs of several zoonotic Brucella species in the region.

Methods for genotyping verotoxin-producing Escherichia coli.

PubMed

Karama, M; Gyles, C L

2010-12-01

Verotoxin-producing Escherichia coli (VTEC) is annually incriminated in more than 100,000 cases of enteric foodborne human disease and in losses amounting to $US 2.5 billion every year. A number of genotyping methods have been developed to track VTEC infections and determine diversity and evolutionary relationships among these microorganisms. These methods have facilitated monitoring and surveillance of foodborne VTEC outbreaks and early identification of outbreaks or clusters of outbreaks. Pulsed-field gel electrophoresis (PFGE) has been used extensively to track and differentiate VTEC because of its high discriminatory power, reproducibility and ease of standardization. Multiple-locus variable-number tandem-repeats analysis (MLVA) and microarrays are the latest genotyping methods that have been applied to discriminate VTEC. MLVA, a simpler and less expensive method, is proving to have a discriminatory power comparable to that of PFGE. Microarrays are successfully being applied to differentiate VTEC and make inferences on genome diversification. Novel methods that are being evaluated for subtyping VTEC include the detection of single nucleotide polymorphisms and optical mapping. This review discusses the principles, applications, advantages and disadvantages of genotyping methods that have been used to differentiate VTEC strains. These methods have been mainly used to differentiate strains of O157:H7 VTEC and to a lesser extent non-O157 VTEC. © 2009 Blackwell Verlag GmbH.

Dogs Leaving the ICU Carry a Very Large Multi-Drug Resistant Enterococcal Population with Capacity for Biofilm Formation and Horizontal Gene Transfer

PubMed Central

Ghosh, Anuradha; Dowd, Scot E.; Zurek, Ludek

2011-01-01

The enterococcal community from feces of seven dogs treated with antibiotics for 2–9 days in the veterinary intensive care unit (ICU) was characterized. Both, culture-based approach and culture-independent 16S rDNA amplicon 454 pyrosequencing, revealed an abnormally large enterococcal community: 1.4±0.8×108 CFU gram−1 of feces and 48.9±11.5% of the total 16,228 sequences, respectively. The diversity of the overall microbial community was very low which likely reflects a high selective antibiotic pressure. The enterococcal diversity based on 210 isolates was also low as represented by Enterococcus faecium (54.6%) and Enterococcus faecalis (45.4%). E. faecium was frequently resistant to enrofloxacin (97.3%), ampicillin (96.5%), tetracycline (84.1%), doxycycline (60.2%), erythromycin (53.1%), gentamicin (48.7%), streptomycin (42.5%), and nitrofurantoin (26.5%). In E. faecalis, resistance was common to tetracycline (59.6%), erythromycin (56.4%), doxycycline (53.2%), and enrofloxacin (31.9%). No resistance was detected to vancomycin, tigecycline, linezolid, and quinupristin/dalfopristin in either species. Many isolates carried virulence traits including gelatinase, aggregation substance, cytolysin, and enterococcal surface protein. All E. faecalis strains were biofilm formers in vitro and this phenotype correlated with the presence of gelE and/or esp. In vitro intra-species conjugation assays demonstrated that E. faecium were capable of transferring tetracycline, doxycycline, streptomycin, gentamicin, and erythromycin resistance traits to human clinical strains. Multi-locus variable number tandem repeat analysis (MLVA) and pulsed-field gel electrophoresis (PFGE) of E. faecium strains showed very low genotypic diversity. Interestingly, three E. faecium clones were shared among four dogs suggesting their nosocomial origin. Furthermore, multi-locus sequence typing (MLST) of nine representative MLVA types revealed that six sequence types (STs) originating from five dogs were identical or closely related to STs of human clinical isolates and isolates from hospital outbreaks. It is recommended to restrict close physical contact between pets released from the ICU and their owners to avoid potential health risks. PMID:21811613

Longitudinal observational study over 38 months of verotoxigenic Escherichia coli O157:H7 status in 126 cattle herds.

PubMed

Widgren, Stefan; Söderlund, Robert; Eriksson, Erik; Fasth, Charlotta; Aspan, Anna; Emanuelson, Ulf; Alenius, Stefan; Lindberg, Ann

2015-10-01

Verotoxigenic Escherichia coli O157:H7 (VTEC O157:H7) is an important zoonotic pathogen capable of causing infections in humans, sometimes with severe symptoms such as hemorrhagic colitis and hemolytic uremic syndrome (HUS). It has been reported that a subgroup of VTEC O157:H7, referred to as clade 8, is overrepresented among HUS cases. Cattle are considered to be the main reservoir of VTEC O157:H7 and infected animals shed the bacteria in feces without showing clinical signs of disease. The aims of the present study were: (1) to better understand how the presence of VTEC O157:H7 in the farm environment changes over an extended period of time, (2) to investigate potential risk factors for the presence of the bacteria, and (3) describe the distribution of MLVA types and specifically the occurrence of the hypervirulent strains (clade 8 strains) of VTEC O157:H7. The farm environment of 126 cattle herds in Sweden were sampled from October 2009 to December 2012 (38 months) using pooled pat and overshoe sampling. Each herd was sampled, on average, on 17 occasions (range=1-20; median=19), at intervals of 64 days (range=7-205; median=58). Verotoxigenic E. coli O157:H7 were detected on one or more occasions in 53% of the herds (n=67). In these herds, the percentage of positive sampling occasions ranged from 6% to 72% (mean=19%; median=17%). Multi-locus variable number tandem repeat analysis (MLVA) typing was performed on isolates from infected herds to identify hypervirulent strains (clade 8). Clustering of MLVA profiles yielded 35 clusters and hypervirulent strains were found in 18 herds; the same cluster was often identified on consecutive samplings and in nearby farms. Using generalized estimating equations, an association was found between the probability of detecting VTEC O157:H7 and status at the preceding sampling, season, herd size, infected neighboring farms and recent introduction of animals. This study showed that the bacteria VTEC O157:H7 were spontaneously cleared from the farm environment in most infected herds over time, and key factors were identified to prevent the spread of VTEC O157:H7 between cattle herds. Copyright © 2015 Elsevier B.V. All rights reserved.

Ten years of surveillance of the Yulong plague focus in China and the molecular typing and source tracing of the isolates.

PubMed

Wang, Peng; Shi, Liyuan; Zhang, Fuxin; Guo, Ying; Zhang, Zhikai; Tan, Hongli; Cui, Zhigang; Ding, Yibo; Liang, Ying; Liang, Yun; Yu, Dongzheng; Xu, Jianguo; Li, Wei; Song, Zhizhong

2018-03-01

Plague, caused by Yersinia pestis, was classified as a reemerging infectious disease by the World Health Organization. The five human pneumonic plague cases in Yulong County in 2005 gave rise to the discovery of a Yulong plague focus in Yunnan province, China. Thereafter, continuous wild rodent plague (sylvatic plague) was identified as the main plague reservoir of this focus. In this study, the epizootics in Yulong focus were described, and three molecular typing methods, including the different region (DFR) analysis, clustered regularly interspaced short palindromic repeats (CRISPRs), and the multiple-locus variable number of tandem repeats (VNTR) analysis (MLVA) (14+12), were used for the molecular typing and source tracing of Y. pestis isolates in the Yulong plague focus. Simultaneously, several isolates from the vicinity of Yunnan were used as controls. The results showed that during the 10-year period from 2006 to 2016, an animal plague epidemic occurred in 6 of those years, and 5 villages underwent an animal plague epidemic within a 30-km2 area of the Yulong plague focus. Searching for dead mice was the most effective monitoring method in this plague focus. No positive sample has been found in 6937 captured live rodents thus far, suggesting that the virulence of strains in the Yulong plague focus is stronger and the survival time of mice is shorter after infection. Strains from Lijiang, Sichuan and Tibet were of the same complex based on a typing analysis of DFR and CRISPR. The genetic relationship of Y. pestis illustrated by MLVA "14+12" demonstrates that Tibet and Sichuan strains evolved from the strains 1.IN2 (Qinghai, 1970 and Tibet, 1976), and Lijiang strains are closer to Batang strains (Batang County in Sichuan province, 2011, Himalaya marmot plague foci) in terms of genetic or phylogenic relationships. In conclusion, we have a deeper understanding of this new plague focus throughout this study, which provides a basis for effective prevention and control.

High Resolution Typing by Whole Genome Mapping Enables Discrimination of LA-MRSA (CC398) Strains and Identification of Transmission Events

PubMed Central

Bosch, Thijs; Verkade, Erwin; van Luit, Martijn; Pot, Bruno; Vauterin, Paul; Burggrave, Ronald; Savelkoul, Paul; Kluytmans, Jan; Schouls, Leo

2013-01-01

After its emergence in 2003, a livestock-associated (LA-)MRSA clade (CC398) has caused an impressive increase in the number of isolates submitted for the Dutch national MRSA surveillance and now comprises 40% of all isolates. The currently used molecular typing techniques have limited discriminatory power for this MRSA clade, which hampers studies on the origin and transmission routes. Recently, a new molecular analysis technique named whole genome mapping was introduced. This method creates high-resolution, ordered whole genome restriction maps that may have potential for strain typing. In this study, we assessed and validated the capability of whole genome mapping to differentiate LA-MRSA isolates. Multiple validation experiments showed that whole genome mapping produced highly reproducible results. Assessment of the technique on two well-documented MRSA outbreaks showed that whole genome mapping was able to confirm one outbreak, but revealed major differences between the maps of a second, indicating that not all isolates belonged to this outbreak. Whole genome mapping of LA-MRSA isolates that were epidemiologically unlinked provided a much higher discriminatory power than spa-typing or MLVA. In contrast, maps created from LA-MRSA isolates obtained during a proven LA-MRSA outbreak were nearly indistinguishable showing that transmission of LA-MRSA can be detected by whole genome mapping. Finally, whole genome maps of LA-MRSA isolates originating from two unrelated veterinarians and their household members showed that veterinarians may carry and transmit different LA-MRSA strains at the same time. No such conclusions could be drawn based spa-typing and MLVA. Although PFGE seems to be suitable for molecular typing of LA-MRSA, WGM provides a much higher discriminatory power. Furthermore, whole genome mapping can provide a comparison with other maps within 2 days after the bacterial culture is received, making it suitable to investigate transmission events and outbreaks caused by LA-MRSA. PMID:23805225

The utility of multiple molecular methods including whole genome sequencing as tools to differentiate Escherichia coli O157:H7 outbreaks.

PubMed

Berenger, Byron M; Berry, Chrystal; Peterson, Trevor; Fach, Patrick; Delannoy, Sabine; Li, Vincent; Tschetter, Lorelee; Nadon, Celine; Honish, Lance; Louie, Marie; Chui, Linda

2015-01-01

A standardised method for determining Escherichia coli O157:H7 strain relatedness using whole genome sequencing or virulence gene profiling is not yet established. We sought to assess the capacity of either high-throughput polymerase chain reaction (PCR) of 49 virulence genes, core-genome single nt variants (SNVs) or k-mer clustering to discriminate between outbreak-associated and sporadic E. coli O157:H7 isolates. Three outbreaks and multiple sporadic isolates from the province of Alberta, Canada were included in the study. Two of the outbreaks occurred concurrently in 2014 and one occurred in 2012. Pulsed-field gel electrophoresis (PFGE) and multilocus variable-number tandem repeat analysis (MLVA) were employed as comparator typing methods. The virulence gene profiles of isolates from the 2012 and 2014 Alberta outbreak events and contemporary sporadic isolates were mostly identical; therefore the set of virulence genes chosen in this study were not discriminatory enough to distinguish between outbreak clusters. Concordant with PFGE and MLVA results, core genome SNV and k-mer phylogenies clustered isolates from the 2012 and 2014 outbreaks as distinct events. k-mer phylogenies demonstrated increased discriminatory power compared with core SNV phylogenies. Prior to the widespread implementation of whole genome sequencing for routine public health use, issues surrounding cost, technical expertise, software standardisation, and data sharing/comparisons must be addressed.

Evaluation of molecular typing of foodborne pathogens in European reference laboratories from 2012 to 2013

PubMed Central

Schjørring, Susanne; Niskanen, Taina; Torpdahl, Mia; Björkman, Jonas T; Nielsen, Eva Møller

2016-01-01

In 2012, the European Centre for Disease Prevention and Control (ECDC) initiated external quality assessment (EQA) schemes for molecular typing including the National Public Health Reference Laboratories in Europe. The overall aim for these EQA schemes was to enhance the European surveillance of food-borne pathogens by evaluating and improving the quality and comparability of molecular typing. The EQAs were organised by Statens Serum Institut (SSI) and included Salmonella enterica subsp. enterica, verocytotoxin-producing Escherichia coli (VTEC) and Listeria monocytogenes. Inter-laboratory comparable pulsed-field gel electrophoresis (PFGE) images were obtained from 10 of 17 of the participating laboratories for Listeria, 15 of 25 for Salmonella, but only nine of 20 for VTEC. Most problems were related to PFGE running conditions and/or incorrect use of image acquisition. Analysis of the gels was done in good accordance with the provided guidelines. Furthermore, we assessed the multilocus variable-number tandem repeat analysis (MLVA) scheme for S. Typhimurium. Of 15 laboratories, nine submitted correct results for all analysed strains, and four had difficulties with one strain only. In conclusion, both PFGE and MLVA are prone to variation in quality, and there is therefore a continuous need for standardisation and validation of laboratory performance for molecular typing methods of food-borne pathogens in the human public health sector. PMID:28006653

Characterization of enterohemorrhagic Escherichia coli O111 and O157 strains isolated from outbreak patients in Japan.

PubMed

Watahiki, Masanori; Isobe, Junko; Kimata, Keiko; Shima, Tomoko; Kanatani, Jun-ichi; Shimizu, Miwako; Nagata, Akihiro; Kawakami, Keiko; Yamada, Mikiko; Izumiya, Hidemasa; Iyoda, Sunao; Morita-Ishihara, Tomoko; Mitobe, Jiro; Terajima, Jun; Ohnishi, Makoto; Sata, Tetsutaro

2014-08-01

In April and May 2011, there was a serious food-poisoning outbreak in Japan caused by enterohemorrhagic Escherichia coli (EHEC) strains O111:H8 and O157:H7 from raw beef dishes at branches of a barbecue restaurant. This outbreak involved 181 infected patients, including 34 hemolytic-uremic syndrome (HUS) cases (19%). Among the 34 HUS patients, 21 developed acute encephalopathy (AE) and 5 died. Patient stool specimens yielded E. coli O111 and O157 strains. We also detected both EHEC O111 stx2 and stx-negative E. coli O111 strains in a stock of meat block from the restaurant. Pulsed-field gel electrophoresis (PFGE) and multilocus variable-number tandem-repeat analysis (MLVA) showed that the stx-negative E. coli O111 isolates were closely related to EHEC O111 stx2 isolates. Although the EHEC O157 strains had diverse stx gene profiles (stx1, stx2, and stx1 stx2), the PFGE and MLVA analyses indicated that these isolates originated from a single clone. Deletion of the Stx2-converting prophage from the EHEC O111 stx2 isolates was frequently observed during in vitro growth, suggesting that strain conversion from an EHEC O111 stx2 to an stx-negative strain may have occurred during infection. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Clostridium difficile Genotypes in Piglet Populations in Germany

PubMed Central

Neubauer, Heinrich; Schmoock, Gernot; Baier, Sylvia; Harlizius, Jürgen; Nienhoff, Hendrik; Brase, Katja; Zimmermann, Stefan; Seyboldt, Christian

2013-01-01

Clostridium difficile was isolated from 147 of 201 (73%) rectal swabs of piglets from 15 farms of Lower Saxony and North Rhine-Westphalia. In 14 farms, 14 to 100% (mean, 78%) of the animals tested were culture positive. The rate of isolation was 68% postpartum, increased to 94% in animals 2 to 14 days of age, and declined to 0% for animals 49 days of age and older. There was no link between isolation and antibiotic treatment or diarrhea of piglets. Strains were assigned to 10 PCR ribotypes, and up to 4 PCR ribotypes were found to be present at the same time on a farm. The closely related PCR ribotypes 078 (55%) and 126 (20%) were most frequently recovered and were present in 13 of the 14 positive farms. The comparison of multilocus VNTR (variable number of tandem repeats) analysis (MLVA) data from this study and previously published data on human, porcine, and bovine PCR ribotype 078 isolates from 5 European countries revealed genetic differences between strains of different geographic origin and confirmed the relatedness of human and porcine C. difficile isolates. This study demonstrated that the human-pathogenic PCR ribotypes 078 and 126 are predominant in piglets in Germany. The results suggest that presence of C. difficile is correlated with animal age but not with antibiotic treatment or clinical disease. MLVA indicated that strains of the same geographical origin are often genetically related and corroborated the hypothesis of a close epidemiological connection between human and porcine C. difficile isolates. PMID:24025903

[Interest of new molecular typing method in the study of hospital transmitted Staphylococcus aureus population].

PubMed

Védy, S; Garnotel, E; Koeck, J-L; Simon, F; Molinier, S; Puidupin, A

2007-11-01

To determinate the origin of acquired S. aureus among hospitalised patients and to evaluate the transmission of strains between health care workers and hopistalised patients. The method chosen is a prospective study in risky clinical yards. Nasal swabing of patients and health care workers has been done to isolate bacterial samples. Caracterisation and comparaison of bacterial strains have been made using their antibiotic resistance profil and a recent molecular genotyping technic named MLVA (Multi Locus Variable Number of Tandem Repeat). It has never been used in such context. One hundred and fifty-seven strains have been isolated. They have been compared while realizing 1900 PCR and agar gel electrophoresis in 10 days. 15 clones were identified. One of them is mainly represented among patient's nasal carriage and acquired strains. As far as antibiotype and agr type are concerned, it is similar to hospital-acquired clone described in Europe with other technics (MRSA, Gentamicine-S agr 1). This clone appears to be also transmitted between health care workers and patients. Although it exists, we can't appreciate the intensity of this transmission. These results don't allow us to proceed to a systematic screening for nasal carriage among our health care workers. This study shows that MLVA could be a reliable molecular typing method, which could be used in every day practice. In our experience, it is as performing as PFGE, more didactic, faster and easier.

An outbreak of Shiga toxin-producing Escherichia coli serogroup O157 linked to a lamb-feeding event.

PubMed

Rowell, S; King, C; Jenkins, C; Dallman, T J; Decraene, V; Lamden, K; Howard, A; Featherstone, C A; Cleary, P

2016-09-01

Fifteen confirmed cases and 15 possible cases of Shiga toxin-producing Escherichia coli (STEC) O157 phage type 21/28 were linked to direct contact with lambs at a 'Lambing Live' event in the North West of England between 29 March and 21 April 2014. Twenty-one (70%) of the cases were female, 23 (77%) were children aged <16 years, of whom 14 (46%) were in the 0-5 years age group. Five children developed haemolytic uraemic syndrome. Multilocus variable number tandem repeat analysis (MLVA) profiles on 14 human cases were indistinguishable, and 6/10 animal isolates had a MLVA profile identical to the outbreak profile. Whole-genome sequencing analysis revealed that all isolates, both human and animal, fell within a 5-single nucleotide polymorphism cluster indicating the isolates belonged to the same point source. On inspection of the premises, extensive and uncontrolled physical contact between visitors and animals was occuring within the animal pens and during bottle-feeding. Public areas were visibly contaminated with animal faeces. Information to visitors, and the infection control awareness demonstrated by staff, was inadequate. Managing the risk to visitors of STEC O157 infection at animal petting events and open farms requires implementation of stringent control measures by the operator, as outlined in the industry code of practice. Enforcement action is sometimes required to prevent high-risk activities taking place at both permanent and temporary attractions.

Temperature-Dependent Growth Modeling of Environmental and Clinical Legionella pneumophila Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) Genotypes

PubMed Central

Sharaby, Yehonatan; Rodríguez-Martínez, Sarah; Oks, Olga; Pecellin, Marina; Mizrahi, Hila; Peretz, Avi; Brettar, Ingrid; Höfle, Manfred G.

2017-01-01

ABSTRACT Legionella pneumophila causes waterborne infections resulting in severe pneumonia. High-resolution genotyping of L. pneumophila isolates can be achieved by multiple-locus variable-number tandem-repeat analysis (MLVA). Recently, we found that different MLVA genotypes of L. pneumophila dominated different sites in a small drinking-water network, with a genotype-related temperature and abundance regime. The present study focuses on understanding the temperature-dependent growth kinetics of the genotypes that dominated the water network. Our aim was to model mathematically the influence of temperature on the growth kinetics of different environmental and clinical L. pneumophila genotypes and to compare it with the influence of their ecological niches. Environmental strains showed a distinct temperature preference, with significant differences among the growth kinetics of the three studied genotypes (Gt4, Gt6, and Gt15). Gt4 strains exhibited superior growth at lower temperatures (25 and 30°C), while Gt15 strains appeared to be best adapted to relatively higher temperatures (42 and 45°C). The temperature-dependent growth traits of the environmental genotypes were consistent with their distribution and temperature preferences in the water network. Clinical isolates exhibited significantly higher growth rates and reached higher maximal cell densities at 37°C and 42°C than the environmental strains. Further research on the growth preferences of L. pneumophila clinical and environmental genotypes will result in a better understanding of their ecological niches in drinking-water systems as well as in the human body. IMPORTANCE Legionella pneumophila is a waterborne pathogen that threatens humans in developed countries. The bacteria inhabit natural and man-made freshwater environments. Here we demonstrate that different environmental L. pneumophila genotypes have different temperature-dependent growth kinetics. Moreover, Legionella strains that belong to the same species but were isolated from environmental and clinical sources possess adaptations for growth at different temperatures. These growth preferences may influence the bacterial colonization at specific ecological niches within the drinking-water network. Adaptations for growth at human body temperatures may facilitate the abilities of some L. pneumophila strains to infect and cause illness in humans. Our findings may be used as a tool to improve Legionella monitoring in drinking-water networks. Risk assessment models for predicting the risk of legionellosis should take into account not only Legionella concentrations but also the temperature-dependent growth kinetics of the isolates. PMID:28159784

First isolation, identification, phenotypic and genotypic characterization of Brucella abortus biovar 3 from dairy cattle in Tanzania.

PubMed

Mathew, C; Stokstad, M; Johansen, T B; Klevar, S; Mdegela, R H; Mwamengele, G; Michel, P; Escobar, L; Fretin, D; Godfroid, J

2015-07-21

Brucellosis is a disease of worldwide public health and economic importance. Successful control is based on knowledge of epidemiology and strains present in an area. In developing countries, most investigations are based on serological assays. This study aimed at investigating a dairy herd experiencing abortions in order to establish within-herd seroprevalence to Brucella spp., identify, characterize Brucella strains by Multiple Loci Variable Number of Tandem Repeats Analysis (MLVA-VNTR) and investigate possible spillover to other species. The within-herd seroprevalence in cattle (n = 200) was 48 % (95 % CI 41-55), using an indirect ELISA, while the Rose Bengal Test (RBT) yielded lower prevalence (21.5 %; 95 % CI 16-27). Two sheep (n = 35) and one goat (n = 50) were seropositive using ELISA while none of the dogs (n = 6) was positive with the RBT. Three Brucella were isolated from an aborted fetus and associated membranes. Real time PCR (IS711), Bruce-ladder and classical biotyping classified the isolates as B. abortus biovar 3. MLVA-VNTR revealed two different but closely related genotypes. The isolates showed unique profiles, providing the first genotypic data from Tanzania. These genotypes were not related to B. abortus biovar 3 reference strain Tulya originally isolated from a human patient in Uganda in 1958, unlike the genotypes isolated and characterized recently in Kenya. High within-herd prevalence, isolation of the pathogen and abortion confirm that B. abortus is circulating in this herd with cattle as reservoir hosts. A low seroprevalence in sheep and goats suggests a spillover of B. abortus from cattle to small ruminants in the herd. This is the first isolation and characterization of B. abortus biovar 3 from a dairy cow with abortion in Tanzania. The origin of the Tanzanian genotypes remain elusive, although they seem to be related to genotypes found in Europe, Turkey and China but not related to B. abortus biovar 3 reference strain or genotypes from Kenya. Importantly, replacement heifers are commonly sourced from large farms like this to smallholder farmers, which poses risk of spread of bacteria to other herds. B. abortus is a significant zoonotic risk and animal health problem in this production system, therefore further studies on humans is recommended.

Development of a robust method for isolation of shiga toxin-positive Escherichia coli (STEC) from fecal, plant, soil and water samples from a leafy greens production region in California.

PubMed

Cooley, Michael B; Jay-Russell, Michele; Atwill, Edward R; Carychao, Diana; Nguyen, Kimberly; Quiñones, Beatriz; Patel, Ronak; Walker, Samarpita; Swimley, Michelle; Pierre-Jerome, Edith; Gordus, Andrew G; Mandrell, Robert E

2013-01-01

During a 2.5-year survey of 33 farms and ranches in a major leafy greens production region in California, 13,650 produce, soil, livestock, wildlife, and water samples were tested for Shiga toxin (stx)-producing Escherichia coli (STEC). Overall, 357 and 1,912 samples were positive for E. coli O157:H7 (2.6%) or non-O157 STEC (14.0%), respectively. Isolates differentiated by O-typing ELISA and multilocus variable number tandem repeat analysis (MLVA) resulted in 697 O157:H7 and 3,256 non-O157 STEC isolates saved for further analysis. Cattle (7.1%), feral swine (4.7%), sediment (4.4%), and water (3.3%) samples were positive for E. coli O157:H7; 7/32 birds, 2/145 coyotes, 3/88 samples from elk also were positive. Non-O157 STEC were at approximately 5-fold higher incidence compared to O157 STEC: cattle (37.9%), feral swine (21.4%), birds (2.4%), small mammals (3.5%), deer or elk (8.3%), water (14.0%), sediment (12.3%), produce (0.3%) and soil adjacent to produce (0.6%). stx1, stx2 and stx1/stx2 genes were detected in 63%, 74% and 35% of STEC isolates, respectively. Subtilase, intimin and hemolysin genes were present in 28%, 25% and 79% of non-O157 STEC, respectively; 23% were of the "Top 6″ O-types. The initial method was modified twice during the study revealing evidence of culture bias based on differences in virulence and O-antigen profiles. MLVA typing revealed a diverse collection of O157 and non-O157 STEC strains isolated from multiple locations and sources and O157 STEC strains matching outbreak strains. These results emphasize the importance of multiple approaches for isolation of non-O157 STEC, that livestock and wildlife are common sources of potentially virulent STEC, and evidence of STEC persistence and movement in a leafy greens production environment.

An outbreak of Salmonella Typhimurium phage type 42 associated with the consumption of raw flour.

PubMed

McCallum, Lisa; Paine, Shevaun; Sexton, Kerry; Dufour, Muriel; Dyet, Kristin; Wilson, Maurice; Campbell, Donald; Bandaranayake, Don; Hope, Virginia

2013-02-01

A cluster of salmonellosis cases caused by Salmonella Typhimurium phage type 42 (STM42) emerged in New Zealand in October 2008. STM42 isolates from a wheat-based poultry feed raw material (broll; i.e., product containing wheat flour and particles of grain) had been identified in the 2 months prior to this cluster. Initial investigations indicated that eating uncooked baking mixture was associated with illness. A case-control study was conducted to test the hypothesis that there was an association between STM42 cases and consumption of raw flour or other baking ingredients. Salmonella isolates from human and non-human sources were compared using pulsed-field gel electrophoresis (PFGE) and multiple-locus variable number tandem repeat analysis (MLVA). Environmental investigations included testing flour and other baking ingredients from case homes, unopened bags of flour purchased from retail stores, and inspection of an implicated flour mill. A case-control study of 39 cases and 66 controls found cases had 4.5 times the odds of consuming uncooked baking mixture as controls (95% confidence interval [CI] 1.6-12.5, p-value 0.001). Examination of individual baking ingredients found that, after adjusting for eggs, flour had an odds ratio (OR) of 5.7 (95% CI 1.1-29.1, p-value 0.035). After adjusting for flour, eggs had an OR of 0.8 (95% CI 0.2-3.4, p-value 0.762). PFGE patterns were identical for all STM42 isolates tested; however, MLVA distinguished isolates that were epidemiologically linked to the cluster. STM42 was recovered from flour taken from four cases' homes, two unopened packs purchased from retail stores and packs from three batches of retrieved (recalled) product. This outbreak was associated with the consumption of uncooked baking mixture containing flour contaminated with STM42. The implicated flour mill initiated a voluntary withdrawal from sale of all batches of flour thought to be contaminated. Media releases informed the public about implicated flour brands and the risks of consuming uncooked baking mixture.

Development of a Robust Method for Isolation of Shiga Toxin-Positive Escherichia coli (STEC) from Fecal, Plant, Soil and Water Samples from a Leafy Greens Production Region in California

PubMed Central

Cooley, Michael B.; Jay-Russell, Michele; Atwill, Edward R.; Carychao, Diana; Nguyen, Kimberly; Quiñones, Beatriz; Patel, Ronak; Walker, Samarpita; Swimley, Michelle; Pierre-Jerome, Edith; Gordus, Andrew G.; Mandrell, Robert E.

2013-01-01

During a 2.5-year survey of 33 farms and ranches in a major leafy greens production region in California, 13,650 produce, soil, livestock, wildlife, and water samples were tested for Shiga toxin (stx)-producing Escherichia coli (STEC). Overall, 357 and 1,912 samples were positive for E. coli O157:H7 (2.6%) or non-O157 STEC (14.0%), respectively. Isolates differentiated by O-typing ELISA and multilocus variable number tandem repeat analysis (MLVA) resulted in 697 O157:H7 and 3,256 non-O157 STEC isolates saved for further analysis. Cattle (7.1%), feral swine (4.7%), sediment (4.4%), and water (3.3%) samples were positive for E. coli O157:H7; 7/32 birds, 2/145 coyotes, 3/88 samples from elk also were positive. Non-O157 STEC were at approximately 5-fold higher incidence compared to O157 STEC: cattle (37.9%), feral swine (21.4%), birds (2.4%), small mammals (3.5%), deer or elk (8.3%), water (14.0%), sediment (12.3%), produce (0.3%) and soil adjacent to produce (0.6%). stx1, stx2 and stx1/stx2 genes were detected in 63%, 74% and 35% of STEC isolates, respectively. Subtilase, intimin and hemolysin genes were present in 28%, 25% and 79% of non-O157 STEC, respectively; 23% were of the “Top 6″ O-types. The initial method was modified twice during the study revealing evidence of culture bias based on differences in virulence and O-antigen profiles. MLVA typing revealed a diverse collection of O157 and non-O157 STEC strains isolated from multiple locations and sources and O157 STEC strains matching outbreak strains. These results emphasize the importance of multiple approaches for isolation of non-O157 STEC, that livestock and wildlife are common sources of potentially virulent STEC, and evidence of STEC persistence and movement in a leafy greens production environment. PMID:23762414

Multiple-locus, variable number of tandem repeat analysis (MLVA) of the fish-pathogen Francisella noatunensis

PubMed Central

2011-01-01

Background Since Francisella noatunensis was first isolated from cultured Atlantic cod in 2004, it has emerged as a global fish pathogen causing disease in both warm and cold water species. Outbreaks of francisellosis occur in several important cultured fish species making a correct management of this disease a matter of major importance. Currently there are no vaccines or treatments available. A strain typing system for use in studies of F. noatunensis epizootics would be an important tool for disease management. However, the high genetic similarity within the Francisella spp. makes strain typing difficult, but such typing of the related human pathogen Francisella tullarensis has been performed successfully by targeting loci with higher genetic variation than the traditional signature sequences. These loci are known as Variable Numbers of Tandem Repeat (VNTR). The aim of this study is to identify possible useful VNTRs in the genome of F. noatunensis. Results Seven polymorphic VNTR loci were identified in the preliminary genome sequence of F. noatunensis ssp. noatunensis GM2212 isolate. These VNTR-loci were sequenced in F. noatunensis isolates collected from Atlantic cod (Gadus morhua) from Norway (n = 21), Three-line grunt (Parapristipoma trilineatum) from Japan (n = 1), Tilapia (Oreochromis spp.) from Indonesia (n = 3) and Atlantic salmon (Salmo salar) from Chile (n = 1). The Norwegian isolates presented in this study show both nine allelic profiles and clades, and that the majority of the farmed isolates belong in two clades only, while the allelic profiles from wild cod are unique. Conclusions VNTRs can be used to separate isolates belonging to both subspecies of F. noatunensis. Low allelic diversity in F. noatunensis isolates from outbreaks in cod culture compared to isolates wild cod, indicate that transmission of these isolates may be a result of human activity. The sequence based MLVA system presented in this study should provide a good starting point for further development of a genotyping system that can be used in studies of epizootics and disease management of francisellosis. PMID:21261955

Multistate outbreak of Salmonella enterica serotype enteritidis infection associated with pet guinea pigs.

PubMed

Bartholomew, Michael L; Heffernan, Richard T; Wright, Jennifer G; Klos, Rachel F; Monson, Timothy; Khan, Sofiya; Trees, Eija; Sabol, Ashley; Willems, Robert A; Flynn, Raymond; Deasy, Marshall P; Jones, Benjamen; Davis, Jeffrey P

2014-06-01

Salmonella causes about one million illnesses annually in the United States. Although most infections result from foodborne exposures, animal contact is an important mode of transmission. We investigated a case of Salmonella enterica serotype Enteritidis (SE) sternal osteomyelitis in a previously healthy child who cared for two recently deceased guinea pigs (GPs). A case was defined as SE pulsed-field gel electrophoresis (PFGE) XbaI pattern JEGX01.0021, BlnI pattern JEGA26.0002 (outbreak strain) infection occurring during 2010 in a patient who reported GP exposure. To locate outbreak strain isolates, PulseNet and the US Department of Agriculture National Veterinary Service Laboratories (NVSL) databases were queried. Outbreak strain isolates underwent multilocus variable-number tandem repeat analysis (MLVA). Traceback and environmental investigations were conducted at homes, stores, and breeder or broker facilities. We detected 10 cases among residents of eight states and four NVSL GP outbreak strain isolates. One patient was hospitalized; none died. The median patient age was 9.5 (range, 1-61) years. Among 10 patients, two purchased GPs at independent stores, and three purchased GPs at different national retail chain (chain A) store locations; three were chain A employees and two reported GP exposures of unknown characterization. MLVA revealed four related patterns. Tracebacks identified four distributors and 92 sources supplying GPs to chain A, including one breeder potentially supplying GPs to all case-associated chain A stores. All environmental samples were Salmonella culture-negative. A definitive SE-contaminated environmental source was not identified. Because GPs can harbor Salmonella, consumers and pet industry personnel should be educated regarding risks.

Typing Discrepancy Between Phenotypic and Molecular Characterization Revealing an Emerging Biovar 9 Variant of Smooth Phage-Resistant B. abortus Strain 8416 in China.

PubMed

Kang, Yao-Xia; Li, Xu-Ming; Piao, Dong-Ri; Tian, Guo-Zhong; Jiang, Hai; Jia, En-Hou; Lin, Liang; Cui, Bu-Yun; Chang, Yung-Fu; Guo, Xiao-Kui; Zhu, Yong-Zhang

2015-01-01

A newly isolated smooth colony morphology phage-resistant strain 8416 isolated from a 45-year-old cattle farm cleaner with clinical features of brucellosis in China was reported. The most unusual phenotype was its resistance to two Brucella phages Tbilisi and Weybridge, but sensitive to Berkeley 2, a pattern similar to that of Brucella melitensis biovar 1. VITEK 2 biochemical identification system found that both strain 8416 and B. melitensis strains shared positive ILATk, but negative in other B. abortus strains. However, routine biochemical and phenotypic characteristics of strain 8416 were most similar to that of B. abortus biovar 9 except CO2 requirement. In addition, multiple PCR molecular typing assays including AMOS-PCR, B. abortus special PCR (B-ab PCR) and a novel sub-biovar typing PCR, indicated that strain 8416 may belong to either biovar 3b or 9 of B. abortus. Surprisingly, further MLVA typing results showed that strain 8416 was most closely related to B. abortus biovar 3 in the Brucella MLVA database, primarily differing in 4 out of 16 screened loci. Therefore, due to the unusual discrepancy between phenotypic (biochemical reactions and particular phage lysis profile) and molecular typing characteristics, strain 8416 could not be exactly classified to any of the existing B. abortus biovars and might be a new variant of B. abortus biovar 9. The present study also indicates that the present phage typing scheme for Brucella sp. is subject to variation and the routine Brucella biovar typing needs further studies.

Inter-hospital outbreak of Klebsiella pneumoniae producing KPC-2 carbapenemase in Ireland.

PubMed

Morris, Dearbháile; Boyle, Fiona; Morris, Carol; Condon, Iris; Delannoy-Vieillard, Anne-Sophie; Power, Lorraine; Khan, Aliya; Morris-Downes, Margaret; Finnegan, Cathriona; Powell, James; Monahan, Regina; Burns, Karen; O'Connell, Nuala; Boyle, Liz; O'Gorman, Alan; Humphreys, Hilary; Brisse, Sylvain; Turton, Jane; Woodford, Neil; Cormican, Martin

2012-10-01

To describe an outbreak of KPC-2-producing Klebsiella pneumoniae with inter-hospital spread and measures taken to control transmission. Between January and March 2011, 13 K. pneumoniae isolates were collected from nine patients at hospital A and two patients at hospital B. Meropenem, imipenem and ertapenem MICs were determined by Etest, carbapenemase production was confirmed by the modified Hodge method and by a disc synergy test, and confirmed carbapenemase producers were tested for the presence of carbapenemase-encoding genes by PCR. PFGE, plasmid analysis, multilocus variable-number tandem-repeat analysis (MLVA) and multilocus sequence typing (MLST) analysis were performed on all or a subset of isolates. Meropenem, imipenem and ertapenem MICs were 4 to >32, 8-32 and >16 mg/L, respectively. PCR and sequencing confirmed the presence of bla(KPC-2). PFGE identified four distinguishable (≥88%) pulsed-field profiles (PFPs). Isolates distinguishable by PFGE had identical MLVA profiles, and MLST analysis indicated all isolates belonged to the ST258 clone. Stringent infection prevention and control measures were implemented. Over a period of almost 8 months no further carbapenemase-producing Enterobacteriaceae (CPE) were isolated. However, KPC-2-producing K. pneumoniae was detected in two further patients in hospital A in August (PFP indistinguishable from previous isolates) and October 2011 (PFP similar to but distinguishable from previous isolates). Stringent infection prevention and control measures help contain CPE in the healthcare setting; however, in the case of hospital A, where CPE appears to be established in the population served, it may be virtually impossible to achieve eradication or avoid reintroduction into the hospital.

An outbreak of Salmonella Typhimurium infections in Denmark, Norway and Sweden, 2008.

PubMed

Bruun, T; Sørensen, G; Forshell, L P; Jensen, T; Nygard, K; Kapperud, G; Lindstedt, B A; Berglund, T; Wingstrand, A; Petersen, R F; Müller, L; Kjelsø, C; Ivarsson, S; Hjertqvist, M; Löfdahl, S; Ethelberg, S

2009-03-12

In November-December 2008, Norway and Denmark independently identified outbreaks of Salmonella Typhimurium infections characterised in the multiple-locus variable number of tandem repeats analysis (MLVA) by a distinct profile. Outbreak investigations were initiated independently in the two countries. In Denmark, a total of 37 cases were identified, and multiple findings of the outbreak strain in pork and pigs within the same supply chain led to the identification of pork in various forms as the source. In Norway, ten cases were identified, and the outbreak investigation quickly indicated meat bought in Sweden as the probable source and the Swedish authorities were alerted. Investigations in Sweden identified four human cases and two isolates from minced meat with the distinct profile. Subsequent trace-back of the meat showed that it most likely originated from Denmark. Through international alert from Norway on 19 December, it became clear that the Danish and Norwegian outbreak strains were identical and, later on, that the source of the outbreaks in all three countries could be traced back to Danish pork. MLVA was instrumental in linking the outbreaks in the different countries and tracing the source. This outbreak illustrates that good international communication channels, early alerting mechanisms, inter-sectoral collaboration between public health and food safety authorities and harmonised molecular typing tools are important for effective identification and management of cross-border outbreaks. Differences in legal requirements for food safety in neighbouring countries may be a challenge in terms of communication with consumers in areas where cross-border shopping is common.

A Shigella sonnei outbreak traced to imported basil--the importance of good typing tools and produce traceability systems, Norway, 2011.

PubMed

Guzman-Herrador, B R; Nilsen, E; Cudjoe, K S; Jensvoll, L; Kvamme, J M; Lindegård Aanstad, A; Lindstedt, B A; Nygård, K; Severinsen, G; Werner-Johansen, Ø; Wester, A L; Wiklund, M; Vold, L

2013-12-05

On 9 October 2011, the University Hospital of North Norway alerted the Norwegian Institute of Public Health (NIPH) about an increase in Shigella sonnei infections in Tromsø. The isolates had an identical ‘multilocus variable-number tandem repeat analysis’ (MLVA) profile. Most cases had consumed food provided by delicatessen X. On 14 October, new S. sonnei cases with the same MLVA-profile were reported from Sarpsborg, south-eastern Norway. An outbreak investigation was started to identify the source and prevent further cases. All laboratory-confirmed cases from both clusters were attempted to be interviewed. In addition, a cohort study was performed among the attendees of a banquet in Tromsø where food from delicatessen X had been served and where some people had reported being ill. A trace-back investigation was initiated. In total, 46 cases were confirmed (Tromsø= 42; Sarpsborg= 4). Having eaten basil pesto sauce or fish soup at the banquet in Tromsø were independent risk factors for disease. Basil pesto was the only common food item that had been consumed by confirmed cases occurring in Tromsø and Sarpsborg. The basil had been imported and delivered to both municipalities by the same supplier. No basil from the specific batch was left on the Norwegian market when it was identified as the likely source. As a result of the multidisciplinary investigation, which helped to identify the source, the Norwegian Food Safety Authority, together with NIPH, planned to develop recommendations for food providers on how to handle fresh plant produce prior to consumption.

First outbreak of VIM-2 metallo-β-lactamase-producing Pseudomonas aeruginosa in The Netherlands: microbiology, epidemiology and clinical outcomes.

PubMed

Van der Bij, A K; Van Mansfeld, R; Peirano, G; Goessens, W H F; Severin, J A; Pitout, J D D; Willems, R; Van Westreenen, M

2011-06-01

This study was designed to investigate the prevalence and characteristics of metallo-β-lactamase (MBL)-producing Pseudomonas aeruginosa in a tertiary care centre in The Netherlands, a country that is considered to have a low prevalence of antibiotic-resistant bacteria. Imipenem-resistant P. aeruginosa isolates cultured from clinical specimens during 2008-2009 were analysed phenotypically and molecularly by polymerase chain reaction (PCR) with sequencing. Genotyping was performed by multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA). Clinical information was obtained by electronic chart review for all patients infected or colonised with an imipenem-resistant P. aeruginosa isolate that was included in the study. In total, 106 imipenem-resistant P. aeruginosa isolates were included. The bla(VIM-2) gene was detected in 35/106 isolates (33%) and was associated with integrons. Compared with non-MBL-producing imipenem-resistant P. aeruginosa, VIM-2 MBL-producing isolates showed higher rates of multidrug resistance. Patients with VIM-2 MBL-producing isolates were more likely to be admitted to the Intensive Care Unit (ICU) and had a higher risk of invasive infection, including development of bacteraemia. MLVA identified two separate VIM-2 MBL-producing clones, responsible for outbreaks in the ICU but also affecting 10 other departments. This is the first reported outbreak of VIM-2 MBL-producing P. aeruginosa in The Netherlands. Once introduced, VIM-2 MBL-producing P. aeruginosa cause significant infections and are easily spread within the hospital setting. Copyright © 2011 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Outbreak of Salmonella enteritidis PT14b gastroenteritis at a restaurant in England: the use of molecular typing to achieve a successful prosecution.

PubMed

Chatt, C; Nicholds-Trainor, D; Scrivener, A; Suleman, S; Harvey, M; Dallman, T; Hawker, J; Sibal, B

2017-10-01

To describe an outbreak of Salmonella enteritidis phage type (PT) 14b in people who had eaten at a restaurant, and the investigation and subsequent prosecution of the food business operator (FBO). The local health protection team and environmental health department formed an outbreak control team to investigate the outbreak. Epidemiological, microbiological, and environmental investigations were undertaken. Epidemiological investigations involved case finding and interviews. Microbiological investigation: stool samples from the suspected cases and environmental samples from the implicated food business were investigated. Salmonella isolates obtained were subjected to multiple locus variable-number tandem repeat analysis (MLVA) profiling and whole genome sequencing. In addition, adenosine triphosphate (ATP) hygiene swab tests were used to verify the quality of cleaning procedures and data loggers were used to determine the water temperature of the mechanical dishwasher. Fifteen cases of illness where the causative agent was shown to be S. enteritidis PT14b were identified, all of whom had eaten at the same restaurant. S. enteritidis PT14b was also identified from three of the 11 food and environmental samples taken at the restaurant and found to have the same MLVA profile as the cases. A case for prosecution was built and the FBO was successfully prosecuted in July 2015. This investigation highlighted that the use of molecular typing as part of thorough epidemiological, microbiological, and environmental investigations can present a robust case for prosecution against restaurants which pose a risk to public health. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Molecular typing of isolates obtained from aborted foetuses in Brucella-free Holstein dairy cattle herd after immunisation with Brucella abortus RB51 vaccine in Egypt.

PubMed

Wareth, Gamal; Melzer, Falk; Böttcher, Denny; El-Diasty, Mohamed; El-Beskawy, Mohamed; Rasheed, Nesma; Schmoock, Gernot; Roesler, Uwe; Sprague, Lisa D; Neubauer, Heinrich

2016-12-01

Bovine brucellosis is endemic in Egypt in spite of application of surveillance and control measures. An increase of abortions was reported in a Holstein dairy cattle herd with 600 animals in Damietta governorate in Egypt after immunisation with Brucella (B.) abortus RB51 vaccine. Twenty one (10.6%) of 197 vaccinated cows aborted after 3 months. All aborted cows had been tested seronegative for brucellosis in the past 3 years. B. abortus was isolated from four foetuses. Conventional biochemical and bacteriological identification and polymerase chain reaction (PCR) confirmed two B. abortus biovar (bv.) 1 smooth and two B. abortus rough strains. None of the B. abortus isolates were identified as RB51. Genotyping analysis by multiple locus of variable number tandem repeats analysis based on 16 markers (MLVA-16) revealed two different profiles with low genetic diversity. B. abortus bv1 was introduced in the herd and caused abortions. Copyright © 2016 Elsevier B.V. All rights reserved.

Prevalence and characterisation of Staphylococcus aureus causing community-acquired skin and soft tissue infections on Java and Bali, Indonesia.

PubMed

Santosaningsih, Dewi; Santoso, Sanarto; Setijowati, Nanik; Rasyid, Harun A; Budayanti, Nyoman S; Suata, Ketut; Widhyatmoko, Dicky B; Purwono, Priyo B; Kuntaman, Kuntaman; Damayanti, Damayanti; Prakoeswa, Cita R S; Laurens, Mitchell; van Nierop, Josephine W I; Nanninga, Geraldine L; Oudenes, Neline; de Regt, Michelle; Snijders, Susan V; Verbrugh, Henri A; Severin, Juliëtte A

2018-01-01

To define the role of Staphylococcus aureus in community settings among patients with skin and soft tissue infections (SSTI) in Indonesia. Staphylococcus aureus were cultured from anterior nares, throat and wounds of 567 ambulatory patients presenting with SSTI. The mecA gene and genes encoding Panton-Valentine leukocidin (PVL; lukF-PV and lukS-PV) and exfoliative toxin (ET; eta and etb) were determined by PCR. Clonal relatedness among methicillin-resistant S. aureus (MRSA) and PVL-positive S. aureus was analysed using multilocus variable-number tandem-repeat analysis (MLVA) typing, and multilocus sequence typing (MLST) for a subset of isolates. Staphylococcal cassette chromosome mec (SCCmec) was determined for all MRSA isolates. Moreover, determinants for S. aureus SSTI, and PVL/ET-positive vs PVL/ET-negative S. aureus were assessed. Staphylococcus aureus were isolated from SSTI wounds of 257 (45.3%) patients, eight (3.1%) of these were MRSA. Genes encoding PVL and ETs were detected in 21.8% and 17.5% of methicillin-susceptible S. aureus (MSSA), respectively. PVL-positive MRSA was not detected. Nasopharyngeal S. aureus carriage was an independent determinant for S. aureus SSTI (odds ratio [OR] 1.8). Primary skin infection (OR 5.4) and previous antibiotic therapy (OR 3.5) were associated with PVL-positive MSSA. Primary skin infection (OR 2.2) was the only factor associated with ET-positive MSSA. MLVA typing revealed two more prevalent MSSA clusters. One ST1-MRSA-SCCmec type IV isolate and a cluster of ST239-MRSA-SCCmec type III were found. Community-acquired SSTI in Indonesia was frequently caused by PVL-positive MSSA, and the hospital-associated ST239-MRSA may have spread from the hospital into the community. © 2017 John Wiley & Sons Ltd.

Investigation of a national outbreak of STEC Escherichia coli O157 using online consumer panel control methods: Great Britain, October 2014.

PubMed

Sinclair, C; Jenkins, C; Warburton, F; Adak, G K; Harris, J P

2017-04-01

In October 2014, Public Health England (PHE) identified cases of Shiga toxin-producing Escherichia coli (STEC) serogroup O157 sharing a multiple locus variable-number tandem repeat analysis (MLVA) profile. We conducted a case-control study using multivariable logistic regression to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) testing a range of exposures. Cases were defined as laboratory-confirmed STEC O157 with the implicated MLVA profile, were UK residents aged ⩾18 years with symptom onset between 25 September and 30 October 2014, and had no history of travel abroad within 5 days of symptom onset. One hundred and two cases were identified. Cases were mostly female (65%; median age 49, range 2-92 years). It was the second largest outbreak seen in England, to date, and a case-control study was conducted using market research panel controls and online survey methods. These methods were instrumental in the rapid data collection and analysis necessary to allow traceback investigations for short shelf-life products. This is a new method of control recruitment and this is the first in which it was a standalone recruitment method. The case-control study suggested a strong association between consumption of a ready-to-eat food and disease (aOR 28, 95% CI 5·0-157) from one retailer. No reactive microbiological testing of food items during the outbreak was possible due to the short shelf-life of the product. Collaboration with industrial bodies is needed to ensure timely traceback exercises to identify contamination events and initiate appropriate and focused microbiological testing and implement control measures.

Genotypes of Mycobacterium tuberculosis in patients at risk of drug resistance in Bolivia.

PubMed

Monteserin, Johana; Camacho, Mirtha; Barrera, Lucía; Palomino, Juan Carlos; Ritacco, Viviana; Martin, Anandi

2013-07-01

Bolivia ranks among the 10 Latin American countries with the highest rates of tuberculosis (TB) and multidrug resistant (MDR) TB. In view of this, and of the lacking information on the population structure of Mycobacterium tuberculosis in the country, we explored genotype associations with drug resistance and clustering by analyzing isolates collected in 2010 from 100 consecutive TB patients at risk of drug resistance in seven of the nine departments in which Bolivia is divided. Fourteen isolates were MDR, 29 had other drug resistance profiles, and 57 were pansusceptible. Spoligotype family distribution was: Haarlem 39.4%, LAM 26.3%, T 22.2%, S 2.0%, X 1.0%, orphan 9.1%, with very low intra-family diversity and absence of Beijing genotypes. We found 66 different MIRU-VNTR patterns; the most frequent corresponded to Multiple Locus Variable Analysis (MLVA) MtbC15 patterns 860, 372 and 873. Twelve clusters, each with identical MIRU-VNTR and spoligotypes, gathered 35 patients. We found no association of genotype with drug resistant or MDR-TB. Clustering associated with SIT 50 and the H3 subfamily to which it belongs (p<0.0001). The largest cluster involved isolates from three departments and displayed a genotype (SIT 50/MLVA 860) previously identified in Bolivian migrants into Spain and Argentina suggesting that this genotype is widespread among Bolivian patients. Our study presents a first overview of M. tuberculosis genotypes at risk of drug resistance circulating in Bolivia. However, results should be taken cautiously because the sample is small and includes a particular subset of M. tuberculosis population. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of an unusual Salmonella phage type DT7a and report of a foodborne outbreak of salmonellosis.

PubMed

Lettini, A A; Saccardin, C; Ramon, E; Longo, A; Cortini, E; Dalla Pozza, M C; Barco, L; Guerra, B; Luzzi, I; Ricci, A

2014-10-17

Salmonella enterica subsp. enterica serovar 4,[5],12,i:- is a monophasic variant of Salmonella Typhimurium and its occurrence has markedly increased in several European countries in the last ten years. In June 2011, an outbreak of Salmonella 4,[5],12,i:- was reported among attendees of a wedding reception in the North-East of Italy. The source of this outbreak was identified as a cooked pork product served during the wedding reception. All Salmonella isolates from humans and the contaminated pork products were identified as Salmonella 4,[5],12,i:- and phage typed as DT7a. Afterwards, the farm where the pigs were raised was identified and sampled, and Salmonella Typhimurium was isolated from swine fecal samples. Despite the difference in serovar, these Salmonella Typhimurium isolates were also phage typed as DT7a. In the present study, Salmonella isolates from animals, humans and pork products during the outbreak investigation were subtyped by pulsed-field gel electrophoresis (PFGE), Multiple-Locus Variable number tandem repeats Analysis (MLVA), and resistance patterns, aiming to identify the most suitable subtyping methods to characterize isolates associated with this outbreak. In addition, a collection of epidemiologically unrelated strains of Salmonella 4,[5],12,i:- and Salmonella Typhimurium sharing the same phage type (DT7a) was similarly characterized in order to investigate their genetic relationship. This study provides a first snapshot of a rare Salmonella phage type, DT7a, associated with both Salmonella 4,[5],12,i:- and Salmonella Typhimurium. Moreover, the study demonstrated that in this specific context MLVA could be a reliable tool to support outbreak investigations as well as to assess the genetic relatedness among Salmonella isolates. Copyright © 2014 Elsevier B.V. All rights reserved.

Effectiveness of deep cleaning followed by hydrogen peroxide decontamination during high Clostridium difficile infection incidence.

PubMed

Best, E L; Parnell, P; Thirkell, G; Verity, P; Copland, M; Else, P; Denton, M; Hobson, R P; Wilcox, M H

2014-05-01

Clostridium difficile infection (CDI) remains an infection control challenge, especially when environmental spore contamination and suboptimal cleaning may increase transmission risk. To substantiate the long-term effectiveness throughout a stroke rehabilitation unit (SRU) of deep cleaning and hydrogen peroxide decontamination (HPD), following a high incidence of CDI. Extensive environmental sampling (342 sites on each occasion) for C. difficile using sponge wipes was performed: before and after deep cleaning with detergent/chlorine agent; immediately following HPD; and on two further occasions, 19 days and 20 weeks following HPD. C. difficile isolates underwent polymerase chain reaction ribotyping and multi-locus variable repeat analysis (MLVA). C. difficile was recovered from 10.8%, 6.1%, 0.9%, 0% and 3.5% of sites at baseline, following deep cleaning, immediately after HPD, and 19 days and 20 weeks after HPD, respectively. C. difficile ribotypes recovered after deep cleaning matched those from CDI cases in the SRU during the previous 10 months. Similarly, 10/12 of the positive sites identified at 20 weeks post-HPD harboured the same C. difficile ribotype (002) and MLVA pattern as the isolate from the first post-HPD CDI case. CDI incidence [number of cases on SRU per 10 months (January-October 2011)] declined from 20 before to seven after the intervention. HPD, after deep cleaning with a detergent/chlorine agent, was highly effective for removing environmental C. difficile contamination. Long-term follow-up demonstrated that a CDI symptomatic patient can rapidly recontaminate the immediate environment. Determining a role for HPD should include long-term cost-effectiveness evaluations. Copyright © 2014 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Subtyping of Clostridium difficile PCR ribotypes 591, 106 and 002, the dominant strain types circulating in Medellin, Colombia.

PubMed

Salazar, Clara Lina; Reyes, Catalina; Cienfuegos-Gallet, Astrid Vanessa; Best, Emma; Atehortua, Santiago; Sierra, Patricia; Correa, Margarita M; Fawley, Warren N; Paredes-Sabja, Daniel; Wilcox, Mark; Gonzalez, Angel

2018-01-01

We aimed to achieve a higher typing resolution within the three dominant Clostridium difficile ribotypes (591,106 and 002) circulating in Colombia. A total of 50 C. difficile isolates we had previously typed by PCR-ribotyping, representing the major three ribotypes circulating in Colombia, were analyzed. Twenty-seven isolates of ribotype 591, 12 of ribotype 106 and 11 of ribotype 002 were subtyped by multiple locus variable-number tandem-repeat analysis (MLVA). The presence of the PaLoc genes (tcdA/tcdB), toxin production in culture and antimicrobial susceptibility were also determined. From the total C. difficile ribotypes analyzed, 20 isolates (74%) of ribotype 591, nine (75%) of ribotype 106 and five (45.5%) of ribotype 002 were recovered from patients with Clostridium difficile infection (CDI). MLVA allowed us to recognize four and two different clonal complexes for ribotypes 591 and 002, respectively, having a summed tandem-repeat difference (STRD) <2, whereas none of the ribotype 106 isolates were grouped in a cluster or clonal complex having a STRD >10. Six ribotype 591 and three ribotype 002 isolates belonging to a defined clonal complex were isolated on the same week in two different hospitals. All ribotypes harbored either tcdA+/tcdB+ or tcdA-/tcdB+ PaLoc genes. Moreover, 94% of the isolates were positive for toxin in culture. All isolates were susceptible to vancomycin and metronidazole, while 75% to 100% of the isolates were resistant to clindamycin, and less than 14.8% of ribotype 591 isolates were resistant to moxifloxacina. No significant differences were found among ribotypes with respect to demographic and clinical patients' data; however, our results demonstrated a high molecular heterogeneity of C. difficile strains circulating in Colombia.

Subtyping of Clostridium difficile PCR ribotypes 591, 106 and 002, the dominant strain types circulating in Medellin, Colombia

PubMed Central

Salazar, Clara Lina; Reyes, Catalina; Cienfuegos-Gallet, Astrid Vanessa; Best, Emma; Atehortua, Santiago; Sierra, Patricia; Correa, Margarita M.; Fawley, Warren N.; Paredes-Sabja, Daniel; Wilcox, Mark

2018-01-01

We aimed to achieve a higher typing resolution within the three dominant Clostridium difficile ribotypes (591,106 and 002) circulating in Colombia. A total of 50 C. difficile isolates we had previously typed by PCR-ribotyping, representing the major three ribotypes circulating in Colombia, were analyzed. Twenty-seven isolates of ribotype 591, 12 of ribotype 106 and 11 of ribotype 002 were subtyped by multiple locus variable-number tandem-repeat analysis (MLVA). The presence of the PaLoc genes (tcdA/tcdB), toxin production in culture and antimicrobial susceptibility were also determined. From the total C. difficile ribotypes analyzed, 20 isolates (74%) of ribotype 591, nine (75%) of ribotype 106 and five (45.5%) of ribotype 002 were recovered from patients with Clostridium difficile infection (CDI). MLVA allowed us to recognize four and two different clonal complexes for ribotypes 591 and 002, respectively, having a summed tandem-repeat difference (STRD) <2, whereas none of the ribotype 106 isolates were grouped in a cluster or clonal complex having a STRD >10. Six ribotype 591 and three ribotype 002 isolates belonging to a defined clonal complex were isolated on the same week in two different hospitals. All ribotypes harbored either tcdA+/tcdB+ or tcdA-/tcdB+ PaLoc genes. Moreover, 94% of the isolates were positive for toxin in culture. All isolates were susceptible to vancomycin and metronidazole, while 75% to 100% of the isolates were resistant to clindamycin, and less than 14.8% of ribotype 591 isolates were resistant to moxifloxacina. No significant differences were found among ribotypes with respect to demographic and clinical patients’ data; however, our results demonstrated a high molecular heterogeneity of C. difficile strains circulating in Colombia. PMID:29649308

The role of the environment in transmission of Dichelobacter nodosus between ewes and their lambs

PubMed Central

Muzafar, Mohd; Calvo-Bado, Leo A.; Green, Laura E.; Smith, Edward M.; Russell, Claire L.; Grogono-Thomas, Rose; Wellington, Elizabeth M.H.

2015-01-01

Dichelobacter nodosus (D. nodosus) is the essential causative agent of footrot in sheep. The current study investigated when D. nodosus was detectable on newborn lambs and possible routes of transmission. Specific qPCR was used to detect and quantify the load of D. nodosus in foot swabs of lambs at birth and 5–13 h post-partum, and their mothers 5–13 h post-partum; and in samples of bedding, pasture, soil and faeces. D. nodosus was not detected on the feet of newborn lambs swabbed at birth, but was detected 5–13 h after birth, once they had stood on bedding containing naturally occurring D. nodosus. Multiple genotypes identified by cloning and sequencing a marker gene, pgrA, and by multi locus variable number tandem repeat analysis (MLVA) of community DNA from swabs on individual feet indicated a mixed population of D. nodosus was present on the feet of both ewes and lambs. There was high variation in pgrA tandem repeat number (between 3 and 21 repeats), and multiple MLVA types. The overall similarity index between the populations on ewes and lambs was 0.45, indicating moderate overlap. Mother offspring pairs shared some alleles but not all, suggesting lambs were infected from sources(s) other than just their mother's feet. We hypothesise that D. nodosus is transferred to the feet of lambs via bedding containing naturally occurring populations of D. nodosus, probably as a result of transfer from the feet of the group of housed ewes. The results support the hypothesis that the environment plays a key role in the transmission of D. nodosus between ewes and lambs. PMID:25953734

Two Distinct Yersinia pestis Populations Causing Plague among Humans in the West Nile Region of Uganda.

PubMed

Respicio-Kingry, Laurel B; Yockey, Brook M; Acayo, Sarah; Kaggwa, John; Apangu, Titus; Kugeler, Kiersten J; Eisen, Rebecca J; Griffith, Kevin S; Mead, Paul S; Schriefer, Martin E; Petersen, Jeannine M

2016-02-01

Plague is a life-threatening disease caused by the bacterium, Yersinia pestis. Since the 1990s, Africa has accounted for the majority of reported human cases. In Uganda, plague cases occur in the West Nile region, near the border with Democratic Republic of Congo. Despite the ongoing risk of contracting plague in this region, little is known about Y. pestis genotypes causing human disease. During January 2004-December 2012, 1,092 suspect human plague cases were recorded in the West Nile region of Uganda. Sixty-one cases were culture-confirmed. Recovered Y. pestis isolates were analyzed using three typing methods, single nucleotide polymorphisms (SNPs), pulsed field gel electrophoresis (PFGE), and multiple variable number of tandem repeat analysis (MLVA) and subpopulations analyzed in the context of associated geographic, temporal, and clinical data for source patients. All three methods separated the 61 isolates into two distinct 1.ANT lineages, which persisted throughout the 9 year period and were associated with differences in elevation and geographic distribution. We demonstrate that human cases of plague in the West Nile region of Uganda are caused by two distinct 1.ANT genetic subpopulations. Notably, all three typing methods used, SNPs, PFGE, and MLVA, identified the two genetic subpopulations, despite recognizing different mutation types in the Y. pestis genome. The geographic and elevation differences between the two subpopulations is suggestive of their maintenance in highly localized enzootic cycles, potentially with differing vector-host community composition. This improved understanding of Y. pestis subpopulations in the West Nile region will be useful for identifying ecologic and environmental factors associated with elevated plague risk.

Epidemiology of a Salmonella enterica subsp. Enterica serovar Typhimurium strain associated with a songbird outbreak.

USGS Publications Warehouse

Blehert, David S.; Hernandez, Sonia M.; Keel, Kevin; Sanchez, Susan; Trees, Eija; ,

2012-01-01

Salmonella enterica subsp. enterica serovar Typhimurium is responsible for the majority of salmonellosis cases worldwide. This Salmonella serovar is also responsible for die-offs in songbird populations. In 2009, there was an S. Typhimurium epizootic reported in pine siskins in the eastern United States. At the time, there was also a human outbreak with this serovar that was associated with contaminated peanuts. As peanuts are also used in wild-bird food, it was hypothesized that the pine siskin epizootic was related to this human outbreak. A comparison of songbird and human S. Typhimurium pulsed-field gel electrophoresis (PFGE) patterns revealed that the epizootic was attributed not to the peanut-associated strain but, rather, to a songbird strain first characterized from an American goldfinch in 1998. This same S. Typhimurium strain (PFGE type A3) was also identified in the PulseNet USA database, accounting for 137 of 77,941 total S. Typhimurium PFGE entries. A second molecular typing method, multiple-locus variable-number tandem-repeat analysis (MLVA), confirmed that the same strain was responsible for the pine siskin epizootic in the eastern United States but was distinct from a genetically related strain isolated from pine siskins in Minnesota. The pine siskin A3 strain was first encountered in May 2008 in an American goldfinch and later in a northern cardinal at the start of the pine siskin epizootic. MLVA also confirmed the clonal nature of S. Typhimurium in songbirds and established that the pine siskin epizootic strain was unique to the finch family. For 2009, the distribution of PFGE type A3 in passerines and humans mirrored the highest population density of pine siskins for the East Coast.

Rise and fall of outbreak-specific clone inside endemic pulsotype of Salmonella 4,[5],12:i:-; insights from high-resolution molecular surveillance in Emilia-Romagna, Italy, 2012 to 2015.

PubMed

Morganti, Marina; Bolzoni, Luca; Scaltriti, Erika; Casadei, Gabriele; Carra, Elena; Rossi, Laura; Gherardi, Paola; Faccini, Fabio; Arrigoni, Norma; Sacchi, Anna Rita; Delledonne, Marco; Pongolini, Stefano

2018-03-01

Background and aimEpidemiology of human non-typhoid salmonellosis is characterised by recurrent emergence of new clones of the pathogen over time. Some clonal lines of Salmonella have shaped epidemiology of the disease at global level, as happened for serotype Enteritidis or, more recently, for Salmonella 4,[5],12:i:-, a monophasic variant of serotype Typhimurium. The same clonal behaviour is recognisable at sub-serotype level where single outbreaks or more generalised epidemics are attributable to defined clones. The aim of this study was to understand the dynamics of a clone of Salmonella 4,[5],12:i:- over a 3-year period (2012-15) in a province of Northern Italy where the clone caused a large outbreak in 2013. Furthermore, the role of candidate outbreak sources was investigated and the accuracy of multilocus variable-number tandem repeat analysis (MLVA) was evaluated. Methods: we retrospectively investigated the outbreak through whole genome sequencing (WGS) and further monitored the outbreak clone for 2 years after its conclusion. Results: The study showed the transient nature of the clone in the population, possibly as a consequence of its occasional expansion in a food-processing facility. We demonstrated that important weaknesses characterise conventional typing methods applied to clonal pathogens such as Salmonella 4,[5],12:i:-, namely lack of accuracy for MLVA and inadequate resolution power for PFGE to be reliably used for clone tracking. Conclusions : The study provided evidence for the remarkable prevention potential of whole genome sequencing used as a routine tool in systems that integrate human, food and animal surveillance.

Coagulase-Negative Staphylococci in Human Milk From Mothers of Preterm Compared With Term Neonates.

PubMed

Soeorg, Hiie; Metsvaht, Tuuli; Eelmäe, Imbi; Metsvaht, Hanna Kadri; Treumuth, Sirli; Merila, Mirjam; Ilmoja, Mari-Liis; Lutsar, Irja

2017-05-01

Human milk is the preferred nutrition for neonates and a source of bacteria. Research aim: The authors aimed to characterize the molecular epidemiology and genetic content of staphylococci in the human milk of mothers of preterm and term neonates. Staphylococci were isolated once per week in the 1st month postpartum from the human milk of mothers of 20 healthy term and 49 preterm neonates hospitalized in the neonatal intensive care unit. Multilocus variable-number tandem-repeats analysis and multilocus sequence typing were used. The presence of the mecA gene, icaA gene of the ica-operon, IS 256, and ACME genetic elements was determined by PCR. The human milk of mothers of preterm compared with term neonates had higher counts of staphylococci but lower species diversity. The human milk of mothers of preterm compared with term neonates more often contained Staphylococcus epidermidis mecA (32.7% vs. 2.6%), icaA (18.8% vs. 6%), IS 256 (7.9% vs. 0.9%), and ACME (15.4% vs. 5.1%), as well as Staphylococcus haemolyticus mecA (90.5% vs. 10%) and IS 256 (61.9% vs. 10%). The overall distribution of multilocus variable-number tandem-repeats analysis (MLVA) types and sequence types was similar between the human milk of mothers of preterm and term neonates, but a few mecA-IS 256-positive MLVA types colonized only mothers of preterm neonates. Maternal hospitalization within 1 month postpartum and the use of an arterial catheter or antibacterial treatment in the neonate increased the odds of harboring mecA-positive staphylococci in human milk. Limiting exposure of mothers of preterm neonates to the hospital could prevent human milk colonization with more pathogenic staphylococci.

Characterization of Genomic Island 3 and Genetic Variability of Chilean Field Strains of Brucella abortus▿

PubMed Central

Céspedes, Sandra; Salgado, Paulina; Valenzuela, Patricio; Vidal, Roberto; Oñate, Angel A.

2011-01-01

One of the capabilities developed by bacteria is the ability to gain large fragments of DNA from other bacteria or to lose portions of their own genomes. Among these exchangeable fragments are the genomic islands (GIs). Nine GIs have been identified in Brucella, and genomic island 3 (GI-3) is shared by two pathogenic species, B. melitensis and B. abortus. GI-3 encodes mostly unknown proteins. One of the aims of this study was to perform pulsed-field gel electrophoresis (PFGE) on field isolates of B. abortus from Chile to determine whether these isolates are clonally related. Furthermore, we focused on the characterization of GI-3, studying its organization and the genetic conservation of the GI-3 sequence using techniques such as tiling-path PCR (TP-PCR) and restriction fragment length polymorphism-PCR (RFLP-PCR). Our results, after PFGE was performed on 69 field isolates of B. abortus from Chile, showed that the strains were genetically homogeneous. To increase the power of genetic discrimination among these strains, we used multiple locus variable-number tandem-repeat (VNTR) analysis with 16 loci (MLVA-16). The results obtained by MLVA-16 showed that the strains of B. abortus were genetically heterogeneous and that most of them clustered according to their geographic origin. Of the genetic loci studied, panel 2B was the one describing the highest diversity in the analysis, as well as locus Bruce19 in panel 2A. In relation to the study of GI-3, our experimental analysis by TP-PCR identified and confirmed that GI-3 is present in all wild strains of B. abortus, demonstrating the high stability of gene cluster GI-3 in Chilean field strains. PMID:21543580

Genotyping of Mycobacterium leprae strains from a region of high endemic leprosy prevalence in India.

PubMed

Lavania, Mallika; Jadhav, Rupendra; Turankar, Ravindra P; Singh, Itu; Nigam, Astha; Sengupta, U

2015-12-01

Leprosy is still a major health problem in India which has the highest number of cases. Multiple locus variable number of tandem repeat analysis (MLVA) and single nucleotide polymorphism (SNP) have been proposed as tools of strain typing for tracking the transmission of leprosy. However, empirical data for a defined population from scale and duration were lacking for studying the transmission chain of leprosy. Seventy slit skin scrapings were collected from Purulia (West Bengal), Miraj (Maharashtra), Shahdara (Delhi), and Naini (UP) hospitals of The Leprosy Mission (TLM). SNP subtyping and MLVA on 10 VNTR loci were applied for the strain typing of Mycobacterium leprae. Along with the strain typing conventional epidemiological investigation was also performed to trace the transmission chain. In addition, phylogenetic analysis was done on variable number of tandem repeat (VNTR) data sets using sequence type analysis and recombinational tests (START) software. START software performs analyses to aid in the investigation of bacterial population structure using multilocus sequence data. These analyses include data summary, lineage assignment, and tests for recombination and selection. Diversity was observed in the cross-sectional survey of isolates obtained from 70 patients. Similarity in fingerprinting profiles observed in specimens of cases from the same family or neighborhood locations indicated a possible common source of infection. The data suggest that these VNTRs including subtyping of SNPs can be used to study the sources and transmission chain in leprosy, which could be very important in monitoring of the disease dynamics in high endemic foci. The present study strongly indicates that multi-case families might constitute epidemic foci and the main source of M. leprae in villages, causing the predominant strain or cluster infection leading to the spread of leprosy in the community. Copyright © 2015 Elsevier B.V. All rights reserved.

Prevalence and molecular characterization of Clostridium difficile isolates from a pig slaughterhouse, pork, and humans in Taiwan.

PubMed

Wu, Ying-Chen; Chen, Chih-Ming; Kuo, Chih-Jung; Lee, Jen-Jie; Chen, Pin-Chun; Chang, Yi-Chih; Chen, Ter-Hsin

2017-02-02

Clostridium difficile causes antibiotic-associated diarrhea in both humans and animals. The ribotype 078, predominant in food animals, is associated with community-acquired C. difficile infection, and C. difficile is suggested to be a foodborne pathogen. Recently, the C. difficile ribotype 078 lineage emerged in patients and pigs in Taiwan. This study aimed to investigate the prevalence and molecular characterization of C. difficile isolated from a pig slaughterhouse, retail meat, ready-to-eat meals, and humans in Taiwan. We collected samples from one slaughterhouse (n=422), 29 retail markets (raw pork, n=62; ready-to-eat pork, n=65), and one hospital (non-diarrheal humans, stool, n=317) in 2015. The isolated C. difficile were subjected to ribotyping and multilocus variable-number tandem-repeat analysis (MLVA). In the slaughterhouse, the isolation rate from carcasses was high (23%, 21/92) and ribotype 126 dominated. Scalding water was found to have C. difficile contamination (44%, 4/9), and two of the seven isolates were ribotype 126. The isolation rates from raw pork and ready-to-eat pork were between 20% and 29%. Ribotypes 126, 127, and 014 were found in raw pork, whereas ribotype 078 was not identified in this study. Eight isolates-seven non-toxigenic isolates and one ribotype 017-were found in non-diarrheal human samples. Notably, MLVA showed that ribotype 126 isolates from the slaughterhouse, pig stool, colons, carcasses, and scalding water were closely genetically related, indicating serious risk for cross-contamination. However, the genetic evidence of foodborne transmission from carcasses to food and humans is still lacking. Copyright © 2016. Published by Elsevier B.V.

Clonal Spread of a Unique Strain of Macrolide-Resistant Mycoplasma Pneumoniae Within a Single Family in Italy.

PubMed

Chironna, Maria; Loconsole, Daniela; De Robertis, Anna Lisa; Morea, Anna; Scalini, Egidio; Quarto, Michele; Tafuri, Silvio; Germinario, Cinzia; Manzionna, Mariano

2016-03-01

Macrolide-resistant Mycoplasma pneumoniae (MR-MP) is an increasing problem worldwide. This study describes the clonal spread of a unique strain of MR-MP within a single family. On January 23, 2015, nasopharyngeal swabs and sputum samples were collected from the index case (a 9-year-old girl) in southern Italy. The patient had pneumonia and was initially treated with clarithromycin. MR-MP infection was suspected due to prolonged symptoms despite appropriate antibiotic therapy. Two further cases of pneumonia occurred in relatives (a 7-year-old cousin and the 36-year-old mother of the index case); therefore, respiratory samples were also collected from other family members. Sequence analysis identified mutations associated with resistance to macrolides. Both P1 major adhesion protein typing and multiple loci variable-number tandem repeat analysis (MLVA) typing were performed to assess the relatedness of the strains. The index case, the cousin, the mother, and another 4 family members (twin siblings of the index case, a 3-year-old cousin, and the grandmother) were positive for MR-MP. All strains harbored the mutation A2063G, had the same P1 subtype (1), and were MLVA (7/4/5/7/2) type Z. In addition, the index case's aunt (31 years of age and the probable source of infection) harbored an M pneumoniae strain with the same molecular profile; however, this strain was susceptible to macrolides. This cluster of MR-MP infection/carriage caused by a clonal strain suggests a high transmission rate within this family and highlights the need for increased awareness among clinicians regarding the circulation of MR-MP. Novel strategies for the treatment and prevention of M pneumoniae infections are required.

Molecular characterization of macrolide resistant Streptococcus pyogenes isolates from pharyngitis patients in Serbia.

PubMed

Opavski, Natasa; Gajic, Ina; Borek, Anna L; Obszańska, Katarzyna; Stanojevic, Maja; Lazarevic, Ivana; Ranin, Lazar; Sitkiewicz, Izabela; Mijac, Vera

2015-07-01

A steady increase in macrolide resistance in Streptococcus pyogenes, group A streptococci (GAS) was reported in Serbia during 2004-2009 (9.9%). However, there are no data on the molecular epidemiology of pharyngeal macrolide resistance GAS (MRGAS) isolates. Therefore, the aims of this first nationwide study were to examine the prevalence of macrolide resistance in Serbian GAS and to determine their resistance phenotypes, genotypes and clonal relationships. Overall 3893 non-duplicate pharyngeal S. pyogenes isolates from outpatients with GAS infection were collected throughout country during 2008 and 2009. Among 486 macrolide resistant pharyngeal isolates collected, 103 were further characterized. Macrolide resistance phenotypes and genotypes were determined by double-disk diffusion test and PCR, respectively. Strain relatedness was determined by emm typing, multilocus sequence typing (MLST), multilocus variable tandem repeat analysis (MLVA), phage profiling (PP) and virulence factor profiling (VFP). Overall, macrolide resistance among GAS isolates in Serbia was 12.5%. M phenotype was the most common (71.8%), followed by iMLS (18.4%) and cMLS (9.7%). Three clonal complexes--emm75/mefA/ST49, emm12/mefA/ST36 and emm77/ermA/tetO/ST63 comprised over 90% of the tested strains. Although MLVA, PP and VFP distinguished 10, 20 and 12 different patterns, respectively, cluster analysis disclosed only small differences between strains which belonged to the same emm/ST type. Our data indicate dominance of three major internationally widely disseminated macrolide resistant clones and a high genetic homogeneity among the Serbian MRGAS population. Continued surveillance of macrolide resistance and clonal composition in MRGAS in Serbia in future is necessary to determine stability of MRGAS clones and to guide therapy strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Shiga Toxin-Producing Escherichia coli O157 Shedding Dynamics in an Australian Beef Herd

PubMed Central

Ahlstrom, Christina; Muellner, Petra; Lammers, Geraldine; Jones, Meghan; Octavia, Sophie; Lan, Ruiting; Heller, Jane

2017-01-01

Shiga toxin-producing Escherichia coli (STEC) O157 is an important foodborne pathogen that can be transmitted to humans both directly and indirectly from the feces of beef cattle, its primary reservoir. Numerous studies have investigated the shedding dynamics of E. coli O157 by beef cattle; however, the spatiotemporal trends of shedding are still not well understood. Molecular tools can increase the resolution through the use of strain typing to explore transmission dynamics within and between herds and identify strain-specific characteristics that may influence pathogenicity and spread. Previously, the shedding dynamics and molecular diversity, through the use of multilocus variable number of tandem repeat analysis (MLVA) of STEC O157, were separately investigated in an Australian beef herd over a 9-month study period. Variation in shedding was observed over time, and 33 MLVA types were identified. The study presented here combines the two datasets previously published with an aim to clarify the relationship between epidemiological variables and strain types. Three major genetic clusters (GCs) were identified that were significantly associated with the location of the cattle in different paddocks. No significant association between GCs and individual cow was observed. Results from this molecular epidemiological study provide evidence for herd-level clonal replacement over time that may have been triggered by movement to a new paddock. In conclusion, this study has provided further insight into STEC O157 shedding dynamics and pathogen transmission. Knowledge gaps remain regarding the relationship of strain types and the shedding dynamics of STEC O157 by beef cattle that could be further clarified through the use of whole-genome sequencing. PMID:29230401

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

River reach classification for the Greater Mekong Region at high spatial resolution

NASA Astrophysics Data System (ADS)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of hydro-ecological assessments and useful for a variety of stakeholders such as NGO, governments and researchers.

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

Land Cover Analysis by Using Pixel-Based and Object-Based Image Classification Method in Bogor

NASA Astrophysics Data System (ADS)

Amalisana, Birohmatin; Rokhmatullah; Hernina, Revi

2017-12-01

The advantage of image classification is to provide earth’s surface information like landcover and time-series changes. Nowadays, pixel-based image classification technique is commonly performed with variety of algorithm such as minimum distance, parallelepiped, maximum likelihood, mahalanobis distance. On the other hand, landcover classification can also be acquired by using object-based image classification technique. In addition, object-based classification uses image segmentation from parameter such as scale, form, colour, smoothness and compactness. This research is aimed to compare the result of landcover classification and its change detection between parallelepiped pixel-based and object-based classification method. Location of this research is Bogor with 20 years range of observation from 1996 until 2016. This region is famous as urban areas which continuously change due to its rapid development, so that time-series landcover information of this region will be interesting.

Diverse Genotypes of Yersinia pestis Caused Plague in Madagascar in 2007.

PubMed

Riehm, Julia M; Projahn, Michaela; Vogler, Amy J; Rajerison, Minoaerisoa; Andersen, Genevieve; Hall, Carina M; Zimmermann, Thomas; Soanandrasana, Rahelinirina; Andrianaivoarimanana, Voahangy; Straubinger, Reinhard K; Nottingham, Roxanne; Keim, Paul; Wagner, David M; Scholz, Holger C

2015-06-01

Yersinia pestis is the causative agent of human plague and is endemic in various African, Asian and American countries. In Madagascar, the disease represents a significant public health problem with hundreds of human cases a year. Unfortunately, poor infrastructure makes outbreak investigations challenging. DNA was extracted directly from 93 clinical samples from patients with a clinical diagnosis of plague in Madagascar in 2007. The extracted DNAs were then genotyped using three molecular genotyping methods, including, single nucleotide polymorphism (SNP) typing, multi-locus variable-number tandem repeat analysis (MLVA), and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) analysis. These methods provided increasing resolution, respectively. The results of these analyses revealed that, in 2007, ten molecular groups, two newly described here and eight previously identified, were responsible for causing human plague in geographically distinct areas of Madagascar. Plague in Madagascar is caused by numerous distinct types of Y. pestis. Genotyping method choice should be based upon the discriminatory power needed, expense, and available data for any desired comparisons. We conclude that genotyping should be a standard tool used in epidemiological investigations of plague outbreaks.

The Evolution of Advanced Molecular Diagnostics for the Detection and Characterization of Mycoplasma pneumoniae.

PubMed

Diaz, Maureen H; Winchell, Jonas M

2016-01-01

Over the past decade there have been significant advancements in the methods used for detecting and characterizing Mycoplasma pneumoniae, a common cause of respiratory illness and community-acquired pneumonia worldwide. The repertoire of available molecular diagnostics has greatly expanded from nucleic acid amplification techniques (NAATs) that encompass a variety of chemistries used for detection, to more sophisticated characterizing methods such as multi-locus variable-number tandem-repeat analysis (MLVA), Multi-locus sequence typing (MLST), matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS), single nucleotide polymorphism typing, and numerous macrolide susceptibility profiling methods, among others. These many molecular-based approaches have been developed and employed to continually increase the level of discrimination and characterization in order to better understand the epidemiology and biology of M. pneumoniae. This review will summarize recent molecular techniques and procedures and lend perspective to how each has enhanced the current understanding of this organism and will emphasize how Next Generation Sequencing may serve as a resource for researchers to gain a more comprehensive understanding of the genomic complexities of this insidious pathogen.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

The generalization ability of online SVM classification based on Markov sampling.

PubMed

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

EPA Science Inventory

Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

The population structure of Vibrio cholerae from the Chandigarh Region of Northern India.

PubMed

Abd El Ghany, Moataz; Chander, Jagadish; Mutreja, Ankur; Rashid, Mamoon; Hill-Cawthorne, Grant A; Ali, Shahjahan; Naeem, Raeece; Thomson, Nicholas R; Dougan, Gordon; Pain, Arnab

2014-07-01

Cholera infection continues to be a threat to global public health. The current cholera pandemic associated with Vibrio cholerae El Tor has now been ongoing for over half a century. Thirty-eight V. cholerae El Tor isolates associated with a cholera outbreak in 2009 from the Chandigarh region of India were characterised by a combination of microbiology, molecular typing and whole-genome sequencing. The genomic analysis indicated that two clones of V. cholera circulated in the region and caused disease during this time. These clones fell into two distinct sub-clades that map independently onto wave 3 of the phylogenetic tree of seventh pandemic V. cholerae El Tor. Sequence analyses of the cholera toxin gene, the Vibrio seventh Pandemic Island II (VSPII) and SXT element correlated with this phylogenetic position of the two clades on the El Tor tree. The clade 2 isolates, characterized by a drug-resistant profile and the expression of a distinct cholera toxin, are closely related to the recent V. cholerae isolated elsewhere, including Haiti, but fell on a distinct branch of the tree, showing they were independent outbreaks. Multi-Locus Sequence Typing (MLST) distinguishes two sequence types among the 38 isolates, that did not correspond to the clades defined by whole-genome sequencing. Multi-Locus Variable-length tandem-nucleotide repeat Analysis (MLVA) identified 16 distinct clusters. The use of whole-genome sequencing enabled the identification of two clones of V. cholerae that circulated during the 2009 Chandigarh outbreak. These clones harboured a similar structure of ICEVchHai1 but differed mainly in the structure of CTX phage and VSPII. The limited capacity of MLST and MLVA to discriminate between the clones that circulated in the 2009 Chandigarh outbreak highlights the value of whole-genome sequencing as a route to the identification of further genetic markers to subtype V. cholerae isolates.

A comparison of extended spectrum β-lactamase producing Escherichia coli from clinical, recreational water and wastewater samples associated in time and location

PubMed Central

Søraas, Arne V.; Arnesen, Lotte S.; Leegaard, Truls M.; Sundsfjord, Arnfinn; Jenum, Pål A.

2017-01-01

Extended spectrum β-lactamase producing Escherichia coli (ESBL-EC) are excreted via effluents and sewage into the environment where they can re-contaminate humans and animals. The aim of this observational study was to detect and quantify ESBL-EC in recreational water and wastewater, and perform a genetic and phenotypic comparative analysis of the environmental strains with geographically associated human urinary ESBL-EC. Recreational fresh- and saltwater samples from four different beaches and wastewater samples from a nearby sewage plant were filtered and cultured on differential and ESBL-selective media. After antimicrobial susceptibility testing and multi-locus variable number of tandem repeats assay (MLVA), selected ESBL-EC strains from recreational water were characterized by whole genome sequencing (WGS) and compared to wastewater and human urine isolates from people living in the same area. We detected ESBL-EC in recreational water samples on 8/20 occasions (40%), representing all sites. The ratio of ESBL-EC to total number of E. coli colony forming units varied from 0 to 3.8%. ESBL-EC were present in all wastewater samples in ratios of 0.56–0.75%. ST131 was most prevalent in urine and wastewater samples, while ST10 dominated in water samples. Eight STs and identical ESBL-EC MLVA-types were detected in all compartments. Clinical ESBL-EC isolates were more likely to be multidrug-resistant (p<0.001). This study confirms that ESBL-EC, including those that are capable of causing human infection, are present in recreational waters where there is a potential for human exposure and subsequent gut colonisation and infection in bathers. Multidrug-resistant E. coli strains are present in urban aquatic environments even in countries where antibiotic consumption in both humans and animals is highly restricted. PMID:29040337

Clonally Related Neisseria gonorrhoeae Isolates with Decreased Susceptibility to the Extended-Spectrum Cephalosporin Cefotaxime in Amsterdam, the Netherlands

PubMed Central

Heymans, Raymond; Bruisten, Sylvia M.; Golparian, Daniel; Unemo, Magnus; de Vries, Henry J. C.

2012-01-01

From 2006 to 2008, Neisseria gonorrhoeae isolates were identified with decreased susceptibility to the extended-spectrum cephalosporin (ESC) cefotaxime among visitors of the Amsterdam sexually transmitted infections (STI) clinic, the Netherlands. Spread, clonality, and characteristics of 202 isolates were examined using antibiograms, conventional penA mosaic gene PCR, and N. gonorrhoeae multiple-locus variable-number tandem repeat analysis (NG-MLVA). A strictly defined subset was further characterized by N. gonorrhoeae multiantigen sequence typing (NG-MAST) and sequencing of ESC resistance determinants (penA, mtrR, and porB1b). Seventy-four N. gonorrhoeae isolates with a cefotaxime MIC of >0.125 μg/ml (group A), 54 with a cefotaxime MIC of 0.125 μg/ml (group B), and a control group of 74 with a cefotaxime MIC of <0.125 μg/ml (group C) were included. Fifty-three clonally related penA mosaic-positive isolates (penicillin-binding protein 2 type XXXIV) were identified in group A (n = 47 isolates; 64%) and B (n = 6 isolates; 11%). The 53 penA mosaic-positive isolates were predominantly NG-MAST ST1407 (87%) and contained an mtrR promoter A deletion (98%) and porB1b alterations G101K/A102N. All were assigned to the same NG-MLVA cluster that comprised in total 56 isolates. A correlation was found between decreased cefotaxime susceptibility and ST1407 that was highly prevalent among visitors of the Amsterdam STI clinic. The rapid spread of this strain, which also has been identified in many other countries, might be facilitated by high-risk sexual behavior and should be monitored closely to identify potential treatment failure. Quality-assured surveillance of ESC susceptibility on the national and international levels and exploration of new drugs and/or strategies for treatment of gonorrhea are crucial. PMID:22214779

Significance of the Identification in the Horn of Africa of an Exceptionally Deep Branching Mycobacterium tuberculosis Clade

PubMed Central

Blouin, Yann; Hauck, Yolande; Soler, Charles; Fabre, Michel; Vong, Rithy; Dehan, Céline; Cazajous, Géraldine; Massoure, Pierre-Laurent; Kraemer, Philippe; Jenkins, Akinbowale; Garnotel, Eric; Pourcel, Christine; Vergnaud, Gilles

2012-01-01

Molecular and phylogeographic studies have led to the definition within the Mycobacterium tuberculosis complex (MTBC) of a number of geotypes and ecotypes showing a preferential geographic location or host preference. The MTBC is thought to have emerged in Africa, most likely the Horn of Africa, and to have spread worldwide with human migrations. Under this assumption, there is a possibility that unknown deep branching lineages are present in this region. We genotyped by spoligotyping and multiple locus variable number of tandem repeats (VNTR) analysis (MLVA) 435 MTBC isolates recovered from patients. Four hundred and eleven isolates were collected in the Republic of Djibouti over a 12 year period, with the other 24 isolates originating from neighbouring countries. All major M. tuberculosis lineages were identified, with only two M. africanum and one M. bovis isolates. Upon comparison with typing data of worldwide origin we observed that several isolates showed clustering characteristics compatible with new deep branching. Whole genome sequencing (WGS) of seven isolates and comparison with available WGS data from 38 genomes distributed in the different lineages confirms the identification of ancestral nodes for several clades and most importantly of one new lineage, here referred to as lineage 7. Investigation of specific deletions confirms the novelty of this lineage, and analysis of its precise phylogenetic position indicates that the other three superlineages constituting the MTBC emerged independently but within a relatively short timeframe from the Horn of Africa. The availability of such strains compared to the predominant lineages and sharing very ancient ancestry will open new avenues for identifying some of the genetic factors responsible for the success of the modern lineages. Additional deep branching lineages may be readily and efficiently identified by large-scale MLVA screening of isolates from sub-Saharan African countries followed by WGS analysis of a few selected isolates. PMID:23300794

Genetic diversity, anti-microbial resistance, plasmid profile and frequency of the Vi antigen in Salmonella Dublin strains isolated in Brazil.

PubMed

Vilela, F P; Frazão, M R; Rodrigues, D P; Costa, R G; Casas, M R T; Fernandes, S A; Falcão, J P; Campioni, F

2018-02-01

Salmonella Dublin is strongly adapted to cattle causing enteritis and/or systemic disease with high rates of mortality. However, it can be sporadically isolated from humans, usually causing serious disease, especially in patients with underlying chronic diseases. The aim of this study was to molecularly type S. Dublin strains isolated from humans and animals in Brazil to verify the diversity of these strains as well as to ascertain possible differences between strains isolated from humans and animals. Moreover, the presence of the capsular antigen Vi and the plasmid profile was characterized in addition to the anti-microbial resistance against 15 drugs. For this reason, 113 S. Dublin strains isolated between 1983 and 2016 from humans (83) and animals (30) in Brazil were typed by PFGE and MLVA. The presence of the capsular antigen Vi was verified by PCR, and the phenotypic expression of the capsular antigen was determined serologically. Also, a plasmid analysis for each strain was carried out. The strains studied were divided into 35 different PFGE types and 89 MLVA-types with a similarity of ≥80% and ≥17.5%, respectively. The plasmid sizes found ranged from 2 to >150 kb and none of the strains studied presented the capsular antigen Vi. Resistance or intermediate resistance was found in 23 strains (20.3%) that were resistant to ampicillin, ciprofloxacin, chloramphenicol, imipenem, nalidixic acid, piperacillin, streptomycin and/or tetracycline. The majority of the S. Dublin strains studied and isolated over a 33-year period may descend from a common subtype that has been contaminating humans and animals in Brazil and able to cause invasive disease even in the absence of the capsular antigen. The higher diversity of resistance phenotypes in human isolates, as compared with animal strains, may be a reflection of the different anti-microbial treatments used to control S. Dublin infections in humans in Brazil. © 2017 Blackwell Verlag GmbH.

Distribution of genes encoding virulence factors and molecular analysis of Shigella spp. isolated from patients with diarrhea in Kerman, Iran.

PubMed

Hosseini Nave, Hossein; Mansouri, Shahla; Emaneini, Mohammad; Moradi, Mohammad

2016-03-01

Shigella is one of the important causes of diarrhea worldwide. Shigella has several virulence factors contributing in colonization and invasion of epithelial cells and eventually death of host cells. The present study was performed in order to investigate the distribution of virulence factors genes in Shigella spp. isolated from patients with acute diarrhea in Kerman, Iran as well as the genetic relationship of these isolates. A total of 56 isolates including 31 S. flexneri, 18 S. sonnei and 7 S. boydii were evaluated by polymerase chain reaction (PCR) for the presence of 11 virulence genes (ipaH, ial, set1A, set1B, sen, virF, invE, sat, sigA, pic and sepA). Then, the clonal relationship of these strains was analyzed by multilocus variable-number tandem repeat analysis (MLVA) method. All isolates were positive for ipaH gene. The other genes include ial, invE and virF were found in 80.4%, 60.7% and 67.9% of the isolates, respectively. Both set1A and set1B were detected in 32.3% of S. flexneri isolates, whereas 66.1% of the isolates belonging to different serogroup carried sen gene. The sat gene was present in all S. flexneri isolates, but not in the S. sonnei and S. boydii isolates. The result showed, 30.4% of isolates were simultaneously positive and the rest of the isolates were negative for sepA and pic genes. The Shigella isolates were divided into 29 MLVA types. This study, for the first time, investigated distribution of 11 virulence genes in Shigella spp. Our results revealed heterogeneity of virulence genes in different Shigella serogroups. Furthermore, the strains belonging to the same species had little diversity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

PubMed

Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

2015-07-01

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Object based image analysis for the classification of the growth stages of Avocado crop, in Michoacán State, Mexico

NASA Astrophysics Data System (ADS)

Gao, Yan; Marpu, Prashanth; Morales Manila, Luis M.

2014-11-01

This paper assesses the suitability of 8-band Worldview-2 (WV2) satellite data and object-based random forest algorithm for the classification of avocado growth stages in Mexico. We tested both pixel-based with minimum distance (MD) and maximum likelihood (MLC) and object-based with Random Forest (RF) algorithm for this task. Training samples and verification data were selected by visual interpreting the WV2 images for seven thematic classes: fully grown, middle stage, and early stage of avocado crops, bare land, two types of natural forests, and water body. To examine the contribution of the four new spectral bands of WV2 sensor, all the tested classifications were carried out with and without the four new spectral bands. Classification accuracy assessment results show that object-based classification with RF algorithm obtained higher overall higher accuracy (93.06%) than pixel-based MD (69.37%) and MLC (64.03%) method. For both pixel-based and object-based methods, the classifications with the four new spectral bands (overall accuracy obtained higher accuracy than those without: overall accuracy of object-based RF classification with vs without: 93.06% vs 83.59%, pixel-based MD: 69.37% vs 67.2%, pixel-based MLC: 64.03% vs 36.05%, suggesting that the four new spectral bands in WV2 sensor contributed to the increase of the classification accuracy.

Five cases of vector-borne Francisella tularensis holarctica infections in south-western Germany and genetic diversity.

PubMed

Borde, Johannes P; Zange, Sabine; Antwerpen, Markus H; Georgi, Enrico; von Buttlar, Heiner; Kern, Winfried V; Rieg, Siegbert

2017-08-01

Tularemia is a rare zoonotic disease in Germany. Francisella tularensis has been isolated previously from ticks in southern Germany underscoring the importance of ticks (Ixodes ricinus) in tularemia transmission, but there have been only few reports from this region with single cases or small case series of tick-borne transmissions of tularemia. We report five cases of non-game animal associated tularemia diagnosed from 2010 to 2016 in southwestern Germany - Baden-Wuerttemberg. Our case series and molecular typing (MLVA) results add published clinical experience to this underdiagnosed disease and consolidate previous findings regarding tick-borne transmission of tularemia and phylogenetic diversity in Germany. Copyright © 2017 Elsevier GmbH. All rights reserved.

Genetic Characterization of Bacillus anthracis 17 JB strain.

PubMed

Seyed-Mohamadi, Sakineh; Moradi Bidhendi, Soheila; Tadayon, Keyvan; Ghaderi, Rainak

2015-06-01

Bacillus anthracis is one of the most homogenous bacteria ever described. Some level of diversity. Bacillus anthracis 17JB is a laboratory strain It is broadly used as a challenge strain in guinea pigs for potency test of anthrax vaccine. This work describes genetic characterization of B. anthracis 17 JB strain using the SNPs and MLVA genotyping. In SNPs typing, the originally French 17JB strain represented the A.Br. 008/009 subgroup. In Levy's genotyping method, 843, 451 and 864 bp long fragments were identified at AA03, AJ03 and AA07 loci, respectively. In the vaccine manufacturer perspective these findings are much valuable on their own account, but similar research is required to extend molecular knowledge of B. anthracis epidemiology in Persia.

Innovative vehicle classification strategies : using LIDAR to do more for less.

DOT National Transportation Integrated Search

2012-06-23

This study examines LIDAR (light detection and ranging) based vehicle classification and classification : performance monitoring. First, we develop a portable LIDAR based vehicle classification system that can : be rapidly deployed, and then we use t...

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Classification of weld defect based on information fusion technology for radiographic testing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

A Computerized English-Spanish Correlation Index to Five Biomedical Library Classification Schemes Based on MeSH*

PubMed Central

Muench, Eugene V.

1971-01-01

A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. Some benefits and uses of the index are: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added. PMID:5172471

[Land cover classification of Four Lakes Region in Hubei Province based on MODIS and ENVISAT data].

PubMed

Xue, Lian; Jin, Wei-Bin; Xiong, Qin-Xue; Liu, Zhang-Yong

2010-03-01

Based on the differences of back scattering coefficient in ENVISAT ASAR data, a classification was made on the towns, waters, and vegetation-covered areas in the Four Lakes Region of Hubei Province. According to the local cropping systems and phenological characteristics in the region, and by using the discrepancies of the MODIS-NDVI index from late April to early May, the vegetation-covered areas were classified into croplands and non-croplands. The classification results based on the above-mentioned procedure was verified by the classification results based on the ETM data with high spatial resolution. Based on the DEM data, the non-croplands were categorized into forest land and bottomland; and based on the discrepancies of mean NDVI index per month, the crops were identified as mid rice, late rice, and cotton, and the croplands were identified as paddy field and upland field. The land cover classification based on the MODIS data with low spatial resolution was basically consistent with that based on the ETM data with high spatial resolution, and the total error rate was about 13.15% when the classification results based on ETM data were taken as the standard. The utilization of the above-mentioned procedures for large scale land cover classification and mapping could make the fast tracking of regional land cover classification.

Multi-label literature classification based on the Gene Ontology graph.

PubMed

Jin, Bo; Muller, Brian; Zhai, Chengxiang; Lu, Xinghua

2008-12-08

The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators) that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate protein annotation based on the literature.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

PubMed

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Classification guides. 1203.412 Section 1203... Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification authorities...

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Image-classification-based global dimming algorithm for LED backlights in LCDs

NASA Astrophysics Data System (ADS)

Qibin, Feng; Huijie, He; Dong, Han; Lei, Zhang; Guoqiang, Lv

2015-07-01

Backlight dimming can help LCDs reduce power consumption and improve CR. With fixed parameters, dimming algorithm cannot achieve satisfied effects for all kinds of images. The paper introduces an image-classification-based global dimming algorithm. The proposed classification method especially for backlight dimming is based on luminance and CR of input images. The parameters for backlight dimming level and pixel compensation are adaptive with image classifications. The simulation results show that the classification based dimming algorithm presents 86.13% power reduction improvement compared with dimming without classification, with almost same display quality. The prototype is developed. There are no perceived distortions when playing videos. The practical average power reduction of the prototype TV is 18.72%, compared with common TV without dimming.

A Classification of Remote Sensing Image Based on Improved Compound Kernels of Svm

NASA Astrophysics Data System (ADS)

Zhao, Jianing; Gao, Wanlin; Liu, Zili; Mou, Guifen; Lu, Lin; Yu, Lina

The accuracy of RS classification based on SVM which is developed from statistical learning theory is high under small number of train samples, which results in satisfaction of classification on RS using SVM methods. The traditional RS classification method combines visual interpretation with computer classification. The accuracy of the RS classification, however, is improved a lot based on SVM method, because it saves much labor and time which is used to interpret images and collect training samples. Kernel functions play an important part in the SVM algorithm. It uses improved compound kernel function and therefore has a higher accuracy of classification on RS images. Moreover, compound kernel improves the generalization and learning ability of the kernel.

From learning taxonomies to phylogenetic learning: integration of 16S rRNA gene data into FAME-based bacterial classification.

PubMed

Slabbinck, Bram; Waegeman, Willem; Dawyndt, Peter; De Vos, Paul; De Baets, Bernard

2010-01-30

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context.

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

PubMed Central

2010-01-01

Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context. PMID:20113515

The groningen laryngomalacia classification system--based on systematic review and dynamic airway changes.

PubMed

van der Heijden, Martijn; Dikkers, Frederik G; Halmos, Gyorgy B

2015-12-01

Laryngomalacia is the most common cause of dyspnea and stridor in newborn infants. Laryngomalacia is a dynamic change of the upper airway based on abnormally pliable supraglottic structures, which causes upper airway obstruction. In the past, different classification systems have been introduced. Until now no classification system is widely accepted and applied. Our goal is to provide a simple and complete classification system based on systematic literature search and our experiences. Retrospective cohort study with literature review. All patients with laryngomalacia under the age of 5 at time of diagnosis were included. Photo and video documentation was used to confirm diagnosis and characteristics of dynamic airway change. Outcome was compared with available classification systems in literature. Eighty-five patients were included. In contrast to other classification systems, only three typical different dynamic changes have been identified in our series. Two existing classification systems covered 100% of our findings, but there was an unnecessary overlap between different types in most of the systems. Based on our finding, we propose a new a classification system for laryngomalacia, which is purely based on dynamic airway changes. The groningen laryngomalacia classification is a new, simplified classification system with three types, based on purely dynamic laryngeal changes, tested in a tertiary referral center: Type 1: inward collapse of arytenoids cartilages, Type 2: medial displacement of aryepiglottic folds, and Type 3: posterocaudal displacement of epiglottis against the posterior pharyngeal wall. © 2015 Wiley Periodicals, Inc.

Information extraction with object based support vector machines and vegetation indices

NASA Astrophysics Data System (ADS)

Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

2016-07-01

Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

Couple Graph Based Label Propagation Method for Hyperspectral Remote Sensing Data Classification

NASA Astrophysics Data System (ADS)

Wang, X. P.; Hu, Y.; Chen, J.

2018-04-01

Graph based semi-supervised classification method are widely used for hyperspectral image classification. We present a couple graph based label propagation method, which contains both the adjacency graph and the similar graph. We propose to construct the similar graph by using the similar probability, which utilize the label similarity among examples probably. The adjacency graph was utilized by a common manifold learning method, which has effective improve the classification accuracy of hyperspectral data. The experiments indicate that the couple graph Laplacian which unite both the adjacency graph and the similar graph, produce superior classification results than other manifold Learning based graph Laplacian and Sparse representation based graph Laplacian in label propagation framework.

14 CFR § 1203.412 - Classification guides.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Classification guides. § 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

Performance Evaluation of Frequency Transform Based Block Classification of Compound Image Segmentation Techniques

NASA Astrophysics Data System (ADS)

Selwyn, Ebenezer Juliet; Florinabel, D. Jemi

2018-04-01

Compound image segmentation plays a vital role in the compression of computer screen images. Computer screen images are images which are mixed with textual, graphical, or pictorial contents. In this paper, we present a comparison of two transform based block classification of compound images based on metrics like speed of classification, precision and recall rate. Block based classification approaches normally divide the compound images into fixed size blocks of non-overlapping in nature. Then frequency transform like Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are applied over each block. Mean and standard deviation are computed for each 8 × 8 block and are used as features set to classify the compound images into text/graphics and picture/background block. The classification accuracy of block classification based segmentation techniques are measured by evaluation metrics like precision and recall rate. Compound images of smooth background and complex background images containing text of varying size, colour and orientation are considered for testing. Experimental evidence shows that the DWT based segmentation provides significant improvement in recall rate and precision rate approximately 2.3% than DCT based segmentation with an increase in block classification time for both smooth and complex background images.

Sentiment classification technology based on Markov logic networks

NASA Astrophysics Data System (ADS)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

Application of wavelet transformation and adaptive neighborhood based modified backpropagation (ANMBP) for classification of brain cancer

NASA Astrophysics Data System (ADS)

Werdiningsih, Indah; Zaman, Badrus; Nuqoba, Barry

2017-08-01

This paper presents classification of brain cancer using wavelet transformation and Adaptive Neighborhood Based Modified Backpropagation (ANMBP). Three stages of the processes, namely features extraction, features reduction, and classification process. Wavelet transformation is used for feature extraction and ANMBP is used for classification process. The result of features extraction is feature vectors. Features reduction used 100 energy values per feature and 10 energy values per feature. Classifications of brain cancer are normal, alzheimer, glioma, and carcinoma. Based on simulation results, 10 energy values per feature can be used to classify brain cancer correctly. The correct classification rate of proposed system is 95 %. This research demonstrated that wavelet transformation can be used for features extraction and ANMBP can be used for classification of brain cancer.

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

PubMed

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Concept of Smart Cyberspace for Smart Grid Implementation

NASA Astrophysics Data System (ADS)

Zhukovskiy, Y.; Malov, D.

2018-05-01

The concept of Smart Cyberspace for Smart Grid (SG) implementation is presented in the paper. The classification of electromechanical units, based on the amount of analysing data, the classification of electromechanical units, based on the data processing speed; and the classification of computational network organization, based on required resources, are proposed in this paper. The combination of the considered classifications is formalized, which can be further used in organizing and planning of SG.

FIELD TESTS OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED WATERSHED CLASSIFICATION SCHEMES IN THE GREAT LAKES BASIN

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme for two case studies involving 1) Lake Superior tributaries and 2) watersheds of riverine coastal wetlands...

THE WESTERN LAKE SUPERIOR COMPARATIVE WATERSHED FRAMEWORK: A FIELD TEST OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED GEOGRAPHICALLY-INDEPENDENT CLASSIFICATION

EPA Science Inventory

Stratified random selection of watersheds allowed us to compare geographically-independent classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme within the Northern Lakes a...

FIELD TESTS OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED WATERSHED CLASSIFICATION SCHEMED IN THE GREAT LAKES BASIN

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme for two case studies involving 1)Lake Superior tributaries and 2) watersheds of riverine coastal wetlands ...

World Reference Base | FAO SOILS PORTAL | Food and Agriculture

Science.gov Websites

> Soil classification > World Reference Base FAO SOILS PORTAL Survey Assessment Biodiversity Management Degradation/Restoration Policies/Governance Publications Soil properties Soil classification World Reference Base FAO legend USDA soil taxonomy Universal soil classification National Systems Numerical

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

32 CFR 1633.12 - Reconsideration of classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., upon which the classification is based, change or when he finds that the registrant made a... 32 National Defense 6 2010-07-01 2010-07-01 false Reconsideration of classification. 1633.12... ADMINISTRATION OF CLASSIFICATION § 1633.12 Reconsideration of classification. No classification is permanent. The...

32 CFR 1633.12 - Reconsideration of classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., upon which the classification is based, change or when he finds that the registrant made a... 32 National Defense 6 2011-07-01 2011-07-01 false Reconsideration of classification. 1633.12... ADMINISTRATION OF CLASSIFICATION § 1633.12 Reconsideration of classification. No classification is permanent. The...

A review of supervised object-based land-cover image classification

NASA Astrophysics Data System (ADS)

Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

2017-08-01

Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial vehicle) or agricultural sites where it also correlates with the number of targeted classes. More than 95.6% of studies involve an area less than 300 ha, and the spatial resolution of images is predominantly between 0 and 2 m. Furthermore, we identify some methods that may advance supervised object-based image classification. For example, deep learning and type-2 fuzzy techniques may further improve classification accuracy. Lastly, scientists are strongly encouraged to report results of uncertainty studies to further explore the effects of varied factors on supervised object-based image classification.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

NASA Astrophysics Data System (ADS)

Švab Lenarčič, Andreja; Đurić, Nataša; Čotar, Klemen; Ritlop, Klemen; Oštir, Krištof

2016-10-01

It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

[Proposals for social class classification based on the Spanish National Classification of Occupations 2011 using neo-Weberian and neo-Marxist approaches].

PubMed

Domingo-Salvany, Antònia; Bacigalupe, Amaia; Carrasco, José Miguel; Espelt, Albert; Ferrando, Josep; Borrell, Carme

2013-01-01

In Spain, the new National Classification of Occupations (Clasificación Nacional de Ocupaciones [CNO-2011]) is substantially different to the 1994 edition, and requires adaptation of occupational social classes for use in studies of health inequalities. This article presents two proposals to measure social class: the new classification of occupational social class (CSO-SEE12), based on the CNO-2011 and a neo-Weberian perspective, and a social class classification based on a neo-Marxist approach. The CSO-SEE12 is the result of a detailed review of the CNO-2011 codes. In contrast, the neo-Marxist classification is derived from variables related to capital and organizational and skill assets. The proposed CSO-SEE12 consists of seven classes that can be grouped into a smaller number of categories according to study needs. The neo-Marxist classification consists of 12 categories in which home owners are divided into three categories based on capital goods and employed persons are grouped into nine categories composed of organizational and skill assets. These proposals are complemented by a proposed classification of educational level that integrates the various curricula in Spain and provides correspondences with the International Standard Classification of Education. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results.

PubMed

Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

2011-01-01

The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification's priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.

8 CFR 204.306 - Classification as an immediate relative based on a Convention adoption.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 8 Aliens and Nationality 1 2011-01-01 2011-01-01 false Classification as an immediate relative....306 Classification as an immediate relative based on a Convention adoption. (a) Unless 8 CFR 204.309 requires the denial of a Form I-800A or Form I-800, a child is eligible for classification as an immediate...

Spatial Classification of Orchards and Vineyards with High Spatial Resolution Panchromatic Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warner, Timothy; Steinmaus, Karen L.

2005-02-01

New high resolution single spectral band imagery offers the capability to conduct image classifications based on spatial patterns in imagery. A classification algorithm based on autocorrelation patterns was developed to automatically extract orchards and vineyards from satellite imagery. The algorithm was tested on IKONOS imagery over Granger, WA, which resulted in a classification accuracy of 95%.

A discrimlnant function approach to ecological site classification in northern New England

Treesearch

James M. Fincher; Marie-Louise Smith

1994-01-01

Describes one approach to ecologically based classification of upland forest community types of the White and Green Mountain physiographic regions. The classification approach is based on an intensive statistical analysis of the relationship between the communities and soil-site factors. Discriminant functions useful in distinguishing between types based on soil-site...

Classifications for Cesarean Section: A Systematic Review

PubMed Central

Torloni, Maria Regina; Betran, Ana Pilar; Souza, Joao Paulo; Widmer, Mariana; Allen, Tomas; Gulmezoglu, Metin; Merialdi, Mario

2011-01-01

Background Rising cesarean section (CS) rates are a major public health concern and cause worldwide debates. To propose and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification. Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1) identify the main CS classifications used worldwide, 2) analyze advantages and deficiencies of each system. Methods and Findings Three electronic databases were searched for classifications published 1968–2008. Two reviewers independently assessed classifications using a form created based on items rated as important by international experts. Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of categories, reproducibility, implementability) were assessed and graded. Classifications were tested in 12 hypothetical clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications identified. Indications classifications present important limitations and their overall score ranged from 2–9 (maximum grade = 14). Degree of urgency classifications also had several drawbacks (overall scores 6–9). Woman-based classifications performed best (scores 5–14). Other types of classifications require data not routinely collected and may not be relevant in all settings (scores 3–8). Conclusions This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and Robson's classification, in particular, would be in the best position to fulfill current international and local needs and that efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary. PMID:21283801

Building a common pipeline for rule-based document classification.

PubMed

Patterson, Olga V; Ginter, Thomas; DuVall, Scott L

2013-01-01

Instance-based classification of clinical text is a widely used natural language processing task employed as a step for patient classification, document retrieval, or information extraction. Rule-based approaches rely on concept identification and context analysis in order to determine the appropriate class. We propose a five-step process that enables even small research teams to develop simple but powerful rule-based NLP systems by taking advantage of a common UIMA AS based pipeline for classification. Our proposed methodology coupled with the general-purpose solution provides researchers with access to the data locked in clinical text in cases of limited human resources and compact timelines.

Gold-standard for computer-assisted morphological sperm analysis.

PubMed

Chang, Violeta; Garcia, Alejandra; Hitschfeld, Nancy; Härtel, Steffen

2017-04-01

Published algorithms for classification of human sperm heads are based on relatively small image databases that are not open to the public, and thus no direct comparison is available for competing methods. We describe a gold-standard for morphological sperm analysis (SCIAN-MorphoSpermGS), a dataset of sperm head images with expert-classification labels in one of the following classes: normal, tapered, pyriform, small or amorphous. This gold-standard is for evaluating and comparing known techniques and future improvements to present approaches for classification of human sperm heads for semen analysis. Although this paper does not provide a computational tool for morphological sperm analysis, we present a set of experiments for comparing sperm head description and classification common techniques. This classification base-line is aimed to be used as a reference for future improvements to present approaches for human sperm head classification. The gold-standard provides a label for each sperm head, which is achieved by majority voting among experts. The classification base-line compares four supervised learning methods (1- Nearest Neighbor, naive Bayes, decision trees and Support Vector Machine (SVM)) and three shape-based descriptors (Hu moments, Zernike moments and Fourier descriptors), reporting the accuracy and the true positive rate for each experiment. We used Fleiss' Kappa Coefficient to evaluate the inter-expert agreement and Fisher's exact test for inter-expert variability and statistical significant differences between descriptors and learning techniques. Our results confirm the high degree of inter-expert variability in the morphological sperm analysis. Regarding the classification base line, we show that none of the standard descriptors or classification approaches is best suitable for tackling the problem of sperm head classification. We discovered that the correct classification rate was highly variable when trying to discriminate among non-normal sperm heads. By using the Fourier descriptor and SVM, we achieved the best mean correct classification: only 49%. We conclude that the SCIAN-MorphoSpermGS will provide a standard tool for evaluation of characterization and classification approaches for human sperm heads. Indeed, there is a clear need for a specific shape-based descriptor for human sperm heads and a specific classification approach to tackle the problem of high variability within subcategories of abnormal sperm cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple-locus variable-number tandem repeat analysis potentially reveals the existence of two groups of Anaplasma phagocytophilum circulating in cattle in France with different wild reservoirs.

PubMed

Dugat, Thibaud; Zanella, Gina; Véran, Luc; Lesage, Céline; Girault, Guillaume; Durand, Benoît; Lagrée, Anne-Claire; Boulouis, Henri-Jean; Haddad, Nadia

2016-11-22

Anaplasma phagocytophilum is the causative agent of tick-borne fever, a disease with high economic impact for domestic ruminants in Europe. Epidemiological cycles of this species are complex, and involve different ecotypes circulating in various host species. To date, these epidemiological cycles are poorly understood, especially in Europe, as European reservoir hosts (i.e. vertebrate hosts enabling long-term maintenance of the bacterium in the ecosystem), of the bacterium have not yet been clearly identified. In this study, our objective was to explore the presence, the prevalence, and the genetic diversity of A. phagocytophilum in wild animals, in order to better understand their implications as reservoir hosts of this pathogen. The spleens of 101 wild animals were collected from central France and tested for the presence of A. phagocytophilum DNA by msp2 qPCR. Positive samples were then typed by multi-locus variable-number tandem repeat (VNTR) analysis (MLVA), and compared to 179 previously typed A. phagocytophilum samples. Anaplasma phagocytophilum DNA was detected in 82/101 (81.2%) animals including 48/49 red deer (98%), 20/21 roe deer (95.2%), 13/29 wild boars (44.8%), and 1/1 red fox. MLVA enabled the discrimination of two A. phagocytophilum groups: group A contained the majority of A. phagocytophilum from red deer and two thirds of those from cattle, while group B included a human strain and variants from diverse animal species, i.e. sheep, dogs, a horse, the majority of variants from roe deer, and the remaining variants from cattle and red deer. Our results suggest that red deer and roe deer are promising A. phagocytophilum reservoir host candidates. Moreover, we also showed that A. phagocytophilum potentially circulates in at least two epidemiological cycles in French cattle. The first cycle may involve red deer as reservoir hosts and cattle as accidental hosts for Group A strains, whereas the second cycle could involve roe deer as reservoir hosts and at least domestic ruminants, dogs, horses, and humans as accidental hosts for Group B strains.

Norwegian Sheep Are an Important Reservoir for Human-Pathogenic Escherichia coli O26:H11

PubMed Central

Sekse, Camilla; Lindstedt, Bjørn-Arne; Sunde, Marianne; Løbersli, Inger; Urdahl, Anne Margrete; Kapperud, Georg

2012-01-01

A previous national survey of Escherichia coli in Norwegian sheep detected eae-positive (eae+) E. coli O26:H11 isolates in 16.3% (80/491) of the flocks. The purpose of the present study was to evaluate the human-pathogenic potential of these ovine isolates by comparing them with E. coli O26 isolates from humans infected in Norway. All human E. coli O26 isolates studied carried the eae gene and shared flagellar type H11. Two-thirds of the sheep flocks and 95.1% of the patients harbored isolates containing arcA allele type 2 and espK and were classified as enterohemorrhagic E. coli (EHEC) (stx positive) or EHEC-like (stx negative). These isolates were further divided into group A (EspK2 positive), associated with stx2-EDL933 and stcEO103, and group B (EspK1 positive), associated with stx1a. Although the stx genes were more frequently present in isolates from patients (46.3%) than in those from sheep flocks (5%), more than half of the ovine isolates in the EHEC/EHEC-like group had multiple-locus variable number of tandem repeat analysis (MLVA) profiles that were identical to those seen in stx-positive human O26:H11 isolates. This indicates that EHEC-like ovine isolates may be able to acquire stx-carrying bacteriophages and thereby have the possibility to cause serious illness in humans. The remaining one-third of the sheep flocks and two of the patients had isolates fulfilling the criteria for atypical enteropathogenic E. coli (aEPEC): arcA allele type 1 and espK negative (group C). The majority of these ovine isolates showed MLVA profiles not previously seen in E. coli O26:H11 isolates from humans. However, according to their virulence gene profile, the aEPEC ovine isolates should be considered potentially pathogenic for humans. In conclusion, sheep are an important reservoir of human-pathogenic E. coli O26:H11 isolates in Norway. PMID:22492457

Salmonella occurrence and Enterobacteriaceae counts in pig feed ingredients and compound feed from feed mills in Ireland.

PubMed

Burns, Anne Marie; Lawlor, Peadar G; Gardiner, Gillian E; McCabe, Evonne M; Walsh, Des; Mohammed, Manal; Grant, Jim; Duffy, Geraldine

2015-10-01

The purpose of this study was to assess the occurrence of non-typhoidal Salmonellae and Enterobacteriaceae counts in raw ingredients and compound feeds sampled from feed mills manufacturing pig diets. Between November 2012 and September 2013, feed ingredients (n=340) and compound pig feed (n=313) samples were collected from five commercial feed mills and one home compounder at various locations throughout Ireland. Feed ingredients included cereals, vegetable protein sources and by-products of oil extraction and ethanol production. The compound feeds included meal and pelleted feed for all stages of pig production. Samples were analysed for Salmonella using standard enrichment procedures. Recovered isolates were serotyped, characterised for antibiotic resistance and subtyped by multi locus variance analysis (MLVA). Total Enterobacteriaceae counts were also performed. Salmonella was recovered from 2/338 (0.6%) ingredients (wheat and soybean meal), at two of the six mills. Salmonella was also detected in 3/317 (0.95%) compound feeds including pelleted feed which undergoes heat treatment. All isolates recovered from feed ingredient and compound feed samples were verified as Salmonella enterica subsp. enterica serotype (4,[5],12:i:-) that lack the expression of flagellar Phase 2 antigens representing monophasic variants of Salmonella Typhimurium (4,[5],12:i:-). Isolates exhibited resistance to between two and seven antimicrobials. Two distinct MLVA profiles were observed, with the same profile recovered from both feed and ingredients, although these did not originate at the same mill. There was no relationship between the occurrence of Salmonella and a high Enterobacteriaceae counts but it was shown that Enterobacteriaceae counts were significantly lower in pelleted feed (heat treated) than in meal (no heat treatment) and that Enterobacteriaceae counts would be very useful indicator in HACPP programme. Overall, although the prevalence of Salmonella in pig feed and feed ingredients in the present study was low, even minor Salmonella contamination in feed has the potential to affect many herds and may subsequently cause human infection. Furthermore, the recovery of a recently emerged serovar with multi-antibiotic resistance is a potential cause for concern. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of dry chilling on the genetic diversity of Escherichia coli on beef carcasses and on the survival of E. coli and E. coli O157.

PubMed

Visvalingam, Jeyachchandran; Liu, Yang; Yang, Xianqin

2017-03-06

The objective of this study was to examine the effect of dry chilling on the genetic diversity of naturally occurring Escherichia coli on beef carcasses, and to examine whether two populations of E. coli recovered from carcasses during chilling and E. coli O157 differed in their response to desiccation. Isolates of E. coli were obtained from beef carcasses during a 67h dry chilling process and were genotyped using multiple-locus variable-number tandem-repeat analysis (MLVA). Ten E. coli genotypes found only at 0h (group A) and found more than once (group B), as well as five strains of E. coli O157 (group C) were inoculated on stainless steel coupons and their survival was examined after exposure to 75 and 100% relative humidity (RH) at 0 or 35°C for 67h. A total of 450 E. coli isolates were obtained, with 254, 49, 49, 51, 23, 20, and 4 from 0, 1, 2, 4, 6, 8 and 24h of chilling, respectively. No E. coli were recovered at 67h. MLVA of the isolates revealed 173 distinct genotypes. Genetic diversity of E. coli isolates, defined as ratio of the number of isolates to the number of genotypes, remained between 2.3 and 1.3 during the 24h of chilling. All strains inoculated on stainless steel coupons and exposed to 75% RH at 35°C were completely inactivated, irrespective of their groups. Inactivation of E. coli of the three groups was not significantly (P>0.05) different by exposure to 75% RH at 0°C. The findings indicate that the genetic diversity of E. coli on beef carcasses was not affected by dry chilling. In addition, inactivation of E. coli genotypes and E. coli O157 by desiccation on stainless steel simulating dry chilling conditions did not differ significantly (P>0.05). Thus, dry chilling may be used as an effective antimicrobial intervention for beef carcasses. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Mapping forested wetlands in the Great Zhan River Basin through integrating optical, radar, and topographical data classification techniques.

PubMed

Na, X D; Zang, S Y; Wu, C S; Li, W L

2015-11-01

Knowledge of the spatial extent of forested wetlands is essential to many studies including wetland functioning assessment, greenhouse gas flux estimation, and wildlife suitable habitat identification. For discriminating forested wetlands from their adjacent land cover types, researchers have resorted to image analysis techniques applied to numerous remotely sensed data. While with some success, there is still no consensus on the optimal approaches for mapping forested wetlands. To address this problem, we examined two machine learning approaches, random forest (RF) and K-nearest neighbor (KNN) algorithms, and applied these two approaches to the framework of pixel-based and object-based classifications. The RF and KNN algorithms were constructed using predictors derived from Landsat 8 imagery, Radarsat-2 advanced synthetic aperture radar (SAR), and topographical indices. The results show that the objected-based classifications performed better than per-pixel classifications using the same algorithm (RF) in terms of overall accuracy and the difference of their kappa coefficients are statistically significant (p<0.01). There were noticeably omissions for forested and herbaceous wetlands based on the per-pixel classifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (p<0.01) of Kappa coefficient between results performed based on RF and KNN algorithms. The object-based classification using RF provided a more visually adequate distribution of interested land cover types, while the object classifications based on the KNN algorithm showed noticeably commissions for forested wetlands and omissions for agriculture land. This research proves that the object-based classification with RF using optical, radar, and topographical data improved the mapping accuracy of land covers and provided a feasible approach to discriminate the forested wetlands from the other land cover types in forestry area.

Diagnostic discrepancies in retinopathy of prematurity classification

PubMed Central

Campbell, J. Peter; Ryan, Michael C.; Lore, Emily; Tian, Peng; Ostmo, Susan; Jonas, Karyn; Chan, R.V. Paul; Chiang, Michael F.

2016-01-01

Objective To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts. Design Prospective cohort study. Subjects, Participants, and/or Controls 281 infants were identified as part of a multi-center, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO), and obtained wide-angle retinal images, which were independently classified by two study experts. Methods Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and two experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, overall disease category (no ROP, mild ROP, Type II or pre-plus, and Type I) were compared between the two experts, and to the clinical classification obtained by BIO. Main Outcome Measures Inter-expert image-based agreement and image-based vs. ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic. Results 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620/1553 (40%) of comparisons, plus disease classification (including pre-plus) in 287/1553 (18%), zone in 117/1553 (8%), and overall ROP category in 618/1553 (40%). However, agreement for presence vs. absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease. Conclusions The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically-significant disease such as presence vs. absence of type 1 and type 2 disease is high. There were no differences between image-based grading and the clinical exam in the ability to detect clinically-significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared to the clinical exam. PMID:27238376

THE ROLE OF WATERSHED CLASSIFICATION IN DIAGNOSING CAUSES OF BIOLOGICAL IMPAIRMENT

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmention with a gewographically-based classification scheme for two case studies involving 1) Lake Superior tributaries and 2) watersheds of riverine coastal wetlands ...

Classification of cloud fields based on textural characteristics

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1987-01-01

The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.

Molecular cancer classification using a meta-sample-based regularized robust coding method.

PubMed

Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

2014-01-01

Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel classification methods with high efficiency and prediction accuracy are still needed to deal with high dimensionality and small sample size of typical GEP data. Recently the sparse representation (SR) method has been successfully applied to the cancer classification. Nevertheless, its efficiency needs to be improved when analyzing large-scale GEP data. In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea of meta-sample-based cluster method with regularized robust coding (RRC) method. It assumes that the coding residual and the coding coefficient are respectively independent and identically distributed. Similar to meta-sample-based SR classification (MSRC), MRRCC extracts a set of meta-samples from the training samples, and then encodes a testing sample as the sparse linear combination of these meta-samples. The representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Extensive experiments on publicly available GEP datasets demonstrate that the proposed method is more efficient while its prediction accuracy is equivalent to existing MSRC-based methods and better than other state-of-the-art dimension reduction based methods.

A review of classification algorithms for EEG-based brain-computer interfaces.

PubMed

Lotte, F; Congedo, M; Lécuyer, A; Lamarche, F; Arnaldi, B

2007-06-01

In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

Mediterranean Land Use and Land Cover Classification Assessment Using High Spatial Resolution Data

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2016-10-01

Landscape fragmentation is noticeably practiced in Mediterranean regions and imposes substantial complications in several satellite image classification methods. To some extent, high spatial resolution data were able to overcome such complications. For better classification performances in Land Use Land Cover (LULC) mapping, the current research adopts different classification methods comparison for LULC mapping using Sentinel-2 satellite as a source of high spatial resolution. Both of pixel-based and an object-based classification algorithms were assessed; the pixel-based approach employs Maximum Likelihood (ML), Artificial Neural Network (ANN) algorithms, Support Vector Machine (SVM), and, the object-based classification uses the Nearest Neighbour (NN) classifier. Stratified Masking Process (SMP) that integrates a ranking process within the classes based on spectral fluctuation of the sum of the training and testing sites was implemented. An analysis of the overall and individual accuracy of the classification results of all four methods reveals that the SVM classifier was the most efficient overall by distinguishing most of the classes with the highest accuracy. NN succeeded to deal with artificial surface classes in general while agriculture area classes, and forest and semi-natural area classes were segregated successfully with SVM. Furthermore, a comparative analysis indicates that the conventional classification method yielded better accuracy results than the SMP method overall with both classifiers used, ML and SVM.

A Bio-Inspired Herbal Tea Flavour Assessment Technique

PubMed Central

Zakaria, Nur Zawatil Isqi; Masnan, Maz Jamilah; Zakaria, Ammar; Shakaff, Ali Yeon Md

2014-01-01

Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied. PMID:25010697

Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results

PubMed Central

Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

2011-01-01

Purpose The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. Methods The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. Results A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Conclusion Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification’s priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method. PMID:22267934

Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.

PubMed

Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

2011-01-01

This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery

PubMed Central

LI, GUIYING; LU, DENGSHENG; MORAN, EMILIO; HETRICK, SCOTT

2011-01-01

This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms – maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes. PMID:22368311

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2012-01-01

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

A new epileptic seizure classification based exclusively on ictal semiology.

PubMed

Lüders, H; Acharya, J; Baumgartner, C; Benbadis, S; Bleasel, A; Burgess, R; Dinner, D S; Ebner, A; Foldvary, N; Geller, E; Hamer, H; Holthausen, H; Kotagal, P; Morris, H; Meencke, H J; Noachtar, S; Rosenow, F; Sakamoto, A; Steinhoff, B J; Tuxhorn, I; Wyllie, E

1999-03-01

Historically, seizure semiology was the main feature in the differential diagnosis of epileptic syndromes. With the development of clinical EEG, the definition of electroclinical complexes became an essential tool to define epileptic syndromes, particularly focal epileptic syndromes. Modern advances in diagnostic technology, particularly in neuroimaging and molecular biology, now permit better definitions of epileptic syndromes. At the same time detailed studies showed that there does not necessarily exist a one-to-one relationship between epileptic seizures or electroclinical complexes and epileptic syndromes. These developments call for the reintroduction of an epileptic seizure classification based exclusively on clinical semiology, similar to the seizure classifications which were used by neurologists before the introduction of the modern diagnostic methods. This classification of epileptic seizures should always be complemented by an epileptic syndrome classification based on all the available clinical information (clinical history, neurological exam, ictal semiology, EEG, anatomical and functional neuroimaging, etc.). Such an approach is more consistent with mainstream clinical neurology and would avoid the current confusion between the classification of epileptic seizures (which in the International Seizure Classification is actually a classification of electroclinical complexes) and the classification of epileptic syndromes.

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions

PubMed Central

Morton, Lindsay M.; Linet, Martha S.; Clarke, Christina A.; Kadin, Marshall E.; Vajdic, Claire M.; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C.-H.; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R.; Weisenburger, Dennis D.

2010-01-01

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and “in situ” lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications. PMID:20699439

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions.

PubMed

Turner, Jennifer J; Morton, Lindsay M; Linet, Martha S; Clarke, Christina A; Kadin, Marshall E; Vajdic, Claire M; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C-H; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R; Weisenburger, Dennis D

2010-11-18

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.

Cost-effectiveness of a classification-based system for sub-acute and chronic low back pain.

PubMed

Apeldoorn, Adri T; Bosmans, Judith E; Ostelo, Raymond W; de Vet, Henrica C W; van Tulder, Maurits W

2012-07-01

Identifying relevant subgroups in patients with low back pain (LBP) is considered important to guide physical therapy practice and to improve outcomes. The aim of the present study was to assess the cost-effectiveness of a modified version of Delitto's classification-based treatment approach compared with usual physical therapy care in patients with sub-acute and chronic LBP with 1 year follow-up. All patients were classified using the modified version of Delitto's classification-based system and then randomly assigned to receive either classification-based treatment or usual physical therapy care. The main clinical outcomes measured were; global perceived effect, intensity of pain, functional disability and quality of life. Costs were measured from a societal perspective. Multiple imputations were used for missing data. Uncertainty surrounding cost differences and incremental cost-effectiveness ratios was estimated using bootstrapping. Cost-effectiveness planes and cost-effectiveness acceptability curves were estimated. In total, 156 patients were included. The outcome analyses showed a significantly better outcome on global perceived effect favoring the classification-based approach, and no differences between the groups on pain, disability and quality-adjusted life-years. Mean total societal costs for the classification-based group were 2,287, and for the usual physical therapy care group 2,020. The difference was 266 (95% CI -720 to 1,612) and not statistically significant. Cost-effectiveness analyses showed that the classification-based approach was not cost-effective in comparison with usual physical therapy care for any clinical outcome measure. The classification-based treatment approach as used in this study was not cost-effective in comparison with usual physical therapy care in a population of patients with sub-acute and chronic LBP.

Testing random forest classification for identifying lava flows and mapping age groups on a single Landsat 8 image

NASA Astrophysics Data System (ADS)

Li, Long; Solana, Carmen; Canters, Frank; Kervyn, Matthieu

2017-10-01

Mapping lava flows using satellite images is an important application of remote sensing in volcanology. Several volcanoes have been mapped through remote sensing using a wide range of data, from optical to thermal infrared and radar images, using techniques such as manual mapping, supervised/unsupervised classification, and elevation subtraction. So far, spectral-based mapping applications mainly focus on the use of traditional pixel-based classifiers, without much investigation into the added value of object-based approaches and into advantages of using machine learning algorithms. In this study, Nyamuragira, characterized by a series of > 20 overlapping lava flows erupted over the last century, was used as a case study. The random forest classifier was tested to map lava flows based on pixels and objects. Image classification was conducted for the 20 individual flows and for 8 groups of flows of similar age using a Landsat 8 image and a DEM of the volcano, both at 30-meter spatial resolution. Results show that object-based classification produces maps with continuous and homogeneous lava surfaces, in agreement with the physical characteristics of lava flows, while lava flows mapped through the pixel-based classification are heterogeneous and fragmented including much "salt and pepper noise". In terms of accuracy, both pixel-based and object-based classification performs well but the former results in higher accuracies than the latter except for mapping lava flow age groups without using topographic features. It is concluded that despite spectral similarity, lava flows of contrasting age can be well discriminated and mapped by means of image classification. The classification approach demonstrated in this study only requires easily accessible image data and can be applied to other volcanoes as well if there is sufficient information to calibrate the mapping.

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes of features. Preliminary results based on the GLDV textural features alone look promising.

The development of a classification schema for arts-based approaches to knowledge translation.

PubMed

Archibald, Mandy M; Caine, Vera; Scott, Shannon D

2014-10-01

Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts. © 2014 Sigma Theta Tau International.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

A Systematic Approach to Subgroup Classification in Intellectual Disability

ERIC Educational Resources Information Center

Schalock, Robert L.; Luckasson, Ruth

2015-01-01

This article describes a systematic approach to subgroup classification based on a classification framework and sequential steps involved in the subgrouping process. The sequential steps are stating the purpose of the classification, identifying the classification elements, using relevant information, and using clearly stated and purposeful…

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

HYDROLOGIC REGIME CLASSIFICATION OF LAKE MICHIGAN COASTAL RIVERINE WETLANDS BASED ON WATERSHED CHARACTERISTICS

EPA Science Inventory

Classification of wetlands systems is needed not only to establish reference condition, but also to predict the relative sensitivity of different wetland classes. In the current study, we examined the potential for ecoregion- versus flow-based classification strategies to explain...

Classification of large-scale fundus image data sets: a cloud-computing framework.

PubMed

Roychowdhury, Sohini

2016-08-01

Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

A Review of Major Nursing Vocabularies and the Extent to Which They Have the Characteristics Required for Implementation in Computer-based Systems

PubMed Central

Henry, Suzanne Bakken; Warren, Judith J.; Lange, Linda; Button, Patricia

1998-01-01

Building on the work of previous authors, the Computer-based Patient Record Institute (CPRI) Work Group on Codes and Structures has described features of a classification scheme for implementation within a computer-based patient record. The authors of the current study reviewed the evaluation literature related to six major nursing vocabularies (the North American Nursing Diagnosis Association Taxonomy 1, the Nursing Interventions Classification, the Nursing Outcomes Classification, the Home Health Care Classification, the Omaha System, and the International Classification for Nursing Practice) to determine the extent to which the vocabularies include the CPRI features. None of the vocabularies met all criteria. The Omaha System, Home Health Care Classification, and International Classification for Nursing Practice each included five features. Criteria not fully met by any systems were clear and non-redundant representation of concepts, administrative cross-references, syntax and grammar, synonyms, uncertainty, context-free identifiers, and language independence. PMID:9670127

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Macrophage Responses to Epithelial Dysfunction Promote Lung Fibrosis in Aging

DTIC Science & Technology

2017-10-01

alveolar macrophages based on single cell molecular classification in patients with pulmonary fibrosis. We have recruited a planned number of patients...biomarkers expressed by human tissue-resident and monocyte-derived alveolar macrophages based on single cell molecular classification in patients with...identify novel biomarkers expressed by human tissue-resident and monocyte- derived alveolar macrophages based on single cell molecular classification

Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods. 10; Chapter

NASA Technical Reports Server (NTRS)

Myint, Soe W.; Mesev, Victor; Quattrochi, Dale; Wentz, Elizabeth A.

2013-01-01

Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas.

Comparing the MRI-based Goutallier Classification to an experimental quantitative MR spectroscopic fat measurement of the supraspinatus muscle.

PubMed

Gilbert, Fabian; Böhm, Dirk; Eden, Lars; Schmalzl, Jonas; Meffert, Rainer H; Köstler, Herbert; Weng, Andreas M; Ziegler, Dirk

2016-08-22

The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy. MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman's rank correlation. Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01). The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Cancer Pain: A Critical Review of Mechanism-based Classification and Physical Therapy Management in Palliative Care

PubMed Central

Kumar, Senthil P

2011-01-01

Mechanism-based classification and physical therapy management of pain is essential to effectively manage painful symptoms in patients attending palliative care. The objective of this review is to provide a detailed review of mechanism-based classification and physical therapy management of patients with cancer pain. Cancer pain can be classified based upon pain symptoms, pain mechanisms and pain syndromes. Classification based upon mechanisms not only addresses the underlying pathophysiology but also provides us with an understanding behind patient's symptoms and treatment responses. Existing evidence suggests that the five mechanisms – central sensitization, peripheral sensitization, sympathetically maintained pain, nociceptive and cognitive-affective – operate in patients with cancer pain. Summary of studies showing evidence for physical therapy treatment methods for cancer pain follows with suggested therapeutic implications. Effective palliative physical therapy care using a mechanism-based classification model should be tailored to suit each patient's findings, using a biopsychosocial model of pain. PMID:21976851

Interplay of biopharmaceutics, biopharmaceutics drug disposition and salivary excretion classification systems

PubMed Central

Idkaidek, Nasir M.

2013-01-01

The aim of this commentary is to investigate the interplay of Biopharmaceutics Classification System (BCS), Biopharmaceutics Drug Disposition Classification System (BDDCS) and Salivary Excretion Classification System (SECS). BCS first classified drugs based on permeability and solubility for the purpose of predicting oral drug absorption. Then BDDCS linked permeability with hepatic metabolism and classified drugs based on metabolism and solubility for the purpose of predicting oral drug disposition. On the other hand, SECS classified drugs based on permeability and protein binding for the purpose of predicting the salivary excretion of drugs. The role of metabolism, rather than permeability, on salivary excretion is investigated and the results are not in agreement with BDDCS. Conclusion The proposed Salivary Excretion Classification System (SECS) can be used as a guide for drug salivary excretion based on permeability (not metabolism) and protein binding. PMID:24493977

Status of Vegetation Classification in Redwood Ecosystems

Treesearch

Thomas M. Mahony; John D. Stuart

2007-01-01

Vegetation classifications, based primarily on physiognomic variability and canopy dominants and derived principally from remotely sensed imagery, have been completed for the entire redwood range (Eyre 1980, Fox 1989). However, systematic, quantitative, floristic-based vegetation classifications in old-growth redwood forests have not been completed for large portions...

Hydrologic classification of rivers based on cluster analysis of dimensionless hydrologic signatures: Applications for environmental instream flows

NASA Astrophysics Data System (ADS)

Praskievicz, S. J.; Luo, C.

2017-12-01

Classification of rivers is useful for a variety of purposes, such as generating and testing hypotheses about watershed controls on hydrology, predicting hydrologic variables for ungaged rivers, and setting goals for river management. In this research, we present a bottom-up (based on machine learning) river classification designed to investigate the underlying physical processes governing rivers' hydrologic regimes. The classification was developed for the entire state of Alabama, based on 248 United States Geological Survey (USGS) stream gages that met criteria for length and completeness of records. Five dimensionless hydrologic signatures were derived for each gage: slope of the flow duration curve (indicator of flow variability), baseflow index (ratio of baseflow to average streamflow), rising limb density (number of rising limbs per unit time), runoff ratio (ratio of long-term average streamflow to long-term average precipitation), and streamflow elasticity (sensitivity of streamflow to precipitation). We used a Bayesian clustering algorithm to classify the gages, based on the five hydrologic signatures, into distinct hydrologic regimes. We then used classification and regression trees (CART) to predict each gaged river's membership in different hydrologic regimes based on climatic and watershed variables. Using existing geospatial data, we applied the CART analysis to classify ungaged streams in Alabama, with the National Hydrography Dataset Plus (NHDPlus) catchment (average area 3 km2) as the unit of classification. The results of the classification can be used for meeting management and conservation objectives in Alabama, such as developing statewide standards for environmental instream flows. Such hydrologic classification approaches are promising for contributing to process-based understanding of river systems.

New wideband radar target classification method based on neural learning and modified Euclidean metric

NASA Astrophysics Data System (ADS)

Jiang, Yicheng; Cheng, Ping; Ou, Yangkui

2001-09-01

A new method for target classification of high-range resolution radar is proposed. It tries to use neural learning to obtain invariant subclass features of training range profiles. A modified Euclidean metric based on the Box-Cox transformation technique is investigated for Nearest Neighbor target classification improvement. The classification experiments using real radar data of three different aircraft have demonstrated that classification error can reduce 8% if this method proposed in this paper is chosen instead of the conventional method. The results of this paper have shown that by choosing an optimized metric, it is indeed possible to reduce the classification error without increasing the number of samples.

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

A domains-based taxonomy of supported accommodation for people with severe and persistent mental illness.

PubMed

Siskind, Dan; Harris, Meredith; Pirkis, Jane; Whiteford, Harvey

2013-06-01

A lack of definitional clarity in supported accommodation and the absence of a widely accepted system for classifying supported accommodation models creates barriers to service planning and evaluation. We undertook a systematic review of existing supported accommodation classification systems. Using a structured system for qualitative data analysis, we reviewed the stratification features in these classification systems, identified the key elements of supported accommodation and arranged them into domains and dimensions to create a new taxonomy. The existing classification systems were mapped onto the new taxonomy to verify the domains and dimensions. Existing classification systems used either a service-level characteristic or programmatic approach. We proposed a taxonomy based around four domains: duration of tenure; patient characteristics; housing characteristics; and service characteristics. All of the domains in the taxonomy were drawn from the existing classification structures; however, none of the existing classification structures covered all of the domains in the taxonomy. Existing classification systems are regionally based, limited in scope and lack flexibility. A domains-based taxonomy can allow more accurate description of supported accommodation services, aid in identifying the service elements likely to improve outcomes for specific patient populations, and assist in service planning.

Hierarchical Higher Order Crf for the Classification of Airborne LIDAR Point Clouds in Urban Areas

NASA Astrophysics Data System (ADS)

Niemeyer, J.; Rottensteiner, F.; Soergel, U.; Heipke, C.

2016-06-01

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next iteration of the point-based layer. This framework iterates and mutually propagates context to improve the classification results. Potentially wrong decisions can be revised at later stages. The output is a labelled point cloud as well as segments roughly corresponding to object instances. Moreover, we present two new contextual features for the segment classification: the distance and the orientation of a segment with respect to the closest road. It is shown that the classification benefits from these features. In our experiments the hierarchical framework improve the overall accuracies by 2.3% on a point-based level and by 3.0% on a segment-based level, respectively, compared to a purely point-based classification.

A fuzzy hill-climbing algorithm for the development of a compact associative classifier

NASA Astrophysics Data System (ADS)

Mitra, Soumyaroop; Lam, Sarah S.

2012-02-01

Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

Significance of clustering and classification applications in digital and physical libraries

NASA Astrophysics Data System (ADS)

Triantafyllou, Ioannis; Koulouris, Alexandros; Zervos, Spiros; Dendrinos, Markos; Giannakopoulos, Georgios

2015-02-01

Applications of clustering and classification techniques can be proved very significant in both digital and physical (paper-based) libraries. The most essential application, document classification and clustering, is crucial for the content that is produced and maintained in digital libraries, repositories, databases, social media, blogs etc., based on various tags and ontology elements, transcending the traditional library-oriented classification schemes. Other applications with very useful and beneficial role in the new digital library environment involve document routing, summarization and query expansion. Paper-based libraries can benefit as well since classification combined with advanced material characterization techniques such as FTIR (Fourier Transform InfraRed spectroscopy) can be vital for the study and prevention of material deterioration. An improved two-level self-organizing clustering architecture is proposed in order to enhance the discrimination capacity of the learning space, prior to classification, yielding promising results when applied to the above mentioned library tasks.

Behavior Based Social Dimensions Extraction for Multi-Label Classification

PubMed Central

Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

2016-01-01

Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

Computerized Classification Testing with the Rasch Model

ERIC Educational Resources Information Center

Eggen, Theo J. H. M.

2011-01-01

If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

29 CFR 14.3 - DOL Classification Review Committee.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 1 2014-07-01 2013-07-01 true DOL Classification Review Committee. 14.3 Section 14.3 Labor... Classification Review Committee. A DOL Classification Review Committee is hereby established. (a) Composition of... under the Freedom of Information Act, 5 U.S.C. 552, when a proposed denial is based on classification...

An Evaluation of Item Response Theory Classification Accuracy and Consistency Indices

ERIC Educational Resources Information Center

Wyse, Adam E.; Hao, Shiqi

2012-01-01

This article introduces two new classification consistency indices that can be used when item response theory (IRT) models have been applied. The new indices are shown to be related to Rudner's classification accuracy index and Guo's classification accuracy index. The Rudner- and Guo-based classification accuracy and consistency indices are…

Prostate segmentation by sparse representation based classification

PubMed Central

Gao, Yaozong; Liao, Shu; Shen, Dinggang

2012-01-01

Purpose: The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems. Methods: To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by the elastic net in order to obtain a smooth and clear prostate boundary in the classification result. (3) Residue-based linear regression is incorporated to improve the classification performance and to extend SRC from hard classification to soft classification. (4) Iterative SRC is proposed by using context information to iteratively refine the classification results. Results: The proposed method has been comprehensively evaluated on a dataset consisting of 330 CT images from 24 patients. The effectiveness of the extended SRC has been validated by comparing it with the traditional SRC based on the proposed four extensions. The experimental results show that our extended SRC can obtain not only more accurate classification results but also smoother and clearer prostate boundary than the traditional SRC. Besides, the comparison with other five state-of-the-art prostate segmentation methods indicates that our method can achieve better performance than other methods under comparison. Conclusions: The authors have proposed a novel prostate segmentation method based on the sparse representation based classification, which can achieve considerably accurate segmentation results in CT prostate segmentation. PMID:23039673

Prostate segmentation by sparse representation based classification.

PubMed

Gao, Yaozong; Liao, Shu; Shen, Dinggang

2012-10-01

The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems. To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by the elastic net in order to obtain a smooth and clear prostate boundary in the classification result. (3) Residue-based linear regression is incorporated to improve the classification performance and to extend SRC from hard classification to soft classification. (4) Iterative SRC is proposed by using context information to iteratively refine the classification results. The proposed method has been comprehensively evaluated on a dataset consisting of 330 CT images from 24 patients. The effectiveness of the extended SRC has been validated by comparing it with the traditional SRC based on the proposed four extensions. The experimental results show that our extended SRC can obtain not only more accurate classification results but also smoother and clearer prostate boundary than the traditional SRC. Besides, the comparison with other five state-of-the-art prostate segmentation methods indicates that our method can achieve better performance than other methods under comparison. The authors have proposed a novel prostate segmentation method based on the sparse representation based classification, which can achieve considerably accurate segmentation results in CT prostate segmentation.

On-board multispectral classification study

NASA Technical Reports Server (NTRS)

Ewalt, D.

1979-01-01

The factors relating to onboard multispectral classification were investigated. The functions implemented in ground-based processing systems for current Earth observation sensors were reviewed. The Multispectral Scanner, Thematic Mapper, Return Beam Vidicon, and Heat Capacity Mapper were studied. The concept of classification was reviewed and extended from the ground-based image processing functions to an onboard system capable of multispectral classification. Eight different onboard configurations, each with varying amounts of ground-spacecraft interaction, were evaluated. Each configuration was evaluated in terms of turnaround time, onboard processing and storage requirements, geometric and classification accuracy, onboard complexity, and ancillary data required from the ground.

Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

NASA Astrophysics Data System (ADS)

Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

2015-04-01

Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty. The results indicate that uncertainty estimates provide a valuable addition to traditional accuracy assessments and helps the user to allocate error in crop maps.

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module.

PubMed

Rifai Chai; Naik, Ganesh R; Tran, Yvonne; Sai Ho Ling; Craig, Ashley; Nguyen, Hung T

2015-08-01

An electroencephalography (EEG)-based counter measure device could be used for fatigue detection during driving. This paper explores the classification of fatigue and alert states using power spectral density (PSD) as a feature extractor and fuzzy swarm based-artificial neural network (ANN) as a classifier. An independent component analysis of entropy rate bound minimization (ICA-ERBM) is investigated as a novel source separation technique for fatigue classification using EEG analysis. A comparison of the classification accuracy of source separator versus no source separator is presented. Classification performance based on 43 participants without the inclusion of the source separator resulted in an overall sensitivity of 71.67%, a specificity of 75.63% and an accuracy of 73.65%. However, these results were improved after the inclusion of a source separator module, resulting in an overall sensitivity of 78.16%, a specificity of 79.60% and an accuracy of 78.88% (p <; 0.05).

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

PubMed

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Automated classification of articular cartilage surfaces based on surface texture.

PubMed

Stachowiak, G P; Stachowiak, G W; Podsiadlo, P

2006-11-01

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

Ground-based cloud classification by learning stable local binary patterns

NASA Astrophysics Data System (ADS)

Wang, Yu; Shi, Cunzhao; Wang, Chunheng; Xiao, Baihua

2018-07-01

Feature selection and extraction is the first step in implementing pattern classification. The same is true for ground-based cloud classification. Histogram features based on local binary patterns (LBPs) are widely used to classify texture images. However, the conventional uniform LBP approach cannot capture all the dominant patterns in cloud texture images, thereby resulting in low classification performance. In this study, a robust feature extraction method by learning stable LBPs is proposed based on the averaged ranks of the occurrence frequencies of all rotation invariant patterns defined in the LBPs of cloud images. The proposed method is validated with a ground-based cloud classification database comprising five cloud types. Experimental results demonstrate that the proposed method achieves significantly higher classification accuracy than the uniform LBP, local texture patterns (LTP), dominant LBP (DLBP), completed LBP (CLTP) and salient LBP (SaLBP) methods in this cloud image database and under different noise conditions. And the performance of the proposed method is comparable with that of the popular deep convolutional neural network (DCNN) method, but with less computation complexity. Furthermore, the proposed method also achieves superior performance on an independent test data set.

Effects of Estimation Bias on Multiple-Category Classification with an IRT-Based Adaptive Classification Procedure

ERIC Educational Resources Information Center

Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R.

2006-01-01

The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…

The Sequential Probability Ratio Test and Binary Item Response Models

ERIC Educational Resources Information Center

Nydick, Steven W.

2014-01-01

The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

ERIC Educational Resources Information Center

Zwick, Rebecca; Lenaburg, Lubella

2009-01-01

In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

Selective classification for improved robustness of myoelectric control under nonideal conditions.

PubMed

Scheme, Erik J; Englehart, Kevin B; Hudgins, Bernard S

2011-06-01

Recent literature in pattern recognition-based myoelectric control has highlighted a disparity between classification accuracy and the usability of upper limb prostheses. This paper suggests that the conventionally defined classification accuracy may be idealistic and may not reflect true clinical performance. Herein, a novel myoelectric control system based on a selective multiclass one-versus-one classification scheme, capable of rejecting unknown data patterns, is introduced. This scheme is shown to outperform nine other popular classifiers when compared using conventional classification accuracy as well as a form of leave-one-out analysis that may be more representative of real prosthetic use. Additionally, the classification scheme allows for real-time, independent adjustment of individual class-pair boundaries making it flexible and intuitive for clinical use.

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm.

PubMed

Al-Saffar, Ahmed; Awang, Suryanti; Tao, Hai; Omar, Nazlia; Al-Saiagh, Wafaa; Al-Bared, Mohammed

2018-01-01

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm

PubMed Central

Awang, Suryanti; Tao, Hai; Omar, Nazlia; Al-Saiagh, Wafaa; Al-bared, Mohammed

2018-01-01

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach. PMID:29684036

7 CFR 1794.31 - Classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 12 2013-01-01 2013-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

7 CFR 1794.31 - Classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 12 2012-01-01 2012-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

7 CFR 1794.31 - Classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 12 2014-01-01 2013-01-01 true Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

7 CFR 1794.31 - Classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 12 2010-01-01 2010-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

7 CFR 1794.31 - Classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 12 2011-01-01 2011-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

Comparing K-mer based methods for improved classification of 16S sequences.

PubMed

Vinje, Hilde; Liland, Kristian Hovde; Almøy, Trygve; Snipen, Lars

2015-07-01

The need for precise and stable taxonomic classification is highly relevant in modern microbiology. Parallel to the explosion in the amount of sequence data accessible, there has also been a shift in focus for classification methods. Previously, alignment-based methods were the most applicable tools. Now, methods based on counting K-mers by sliding windows are the most interesting classification approach with respect to both speed and accuracy. Here, we present a systematic comparison on five different K-mer based classification methods for the 16S rRNA gene. The methods differ from each other both in data usage and modelling strategies. We have based our study on the commonly known and well-used naïve Bayes classifier from the RDP project, and four other methods were implemented and tested on two different data sets, on full-length sequences as well as fragments of typical read-length. The difference in classification error obtained by the methods seemed to be small, but they were stable and for both data sets tested. The Preprocessed nearest-neighbour (PLSNN) method performed best for full-length 16S rRNA sequences, significantly better than the naïve Bayes RDP method. On fragmented sequences the naïve Bayes Multinomial method performed best, significantly better than all other methods. For both data sets explored, and on both full-length and fragmented sequences, all the five methods reached an error-plateau. We conclude that no K-mer based method is universally best for classifying both full-length sequences and fragments (reads). All methods approach an error plateau indicating improved training data is needed to improve classification from here. Classification errors occur most frequent for genera with few sequences present. For improving the taxonomy and testing new classification methods, the need for a better and more universal and robust training data set is crucial.

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease

PubMed Central

Schmitter, Daniel; Roche, Alexis; Maréchal, Bénédicte; Ribes, Delphine; Abdulkadir, Ahmed; Bach-Cuadra, Meritxell; Daducci, Alessandro; Granziera, Cristina; Klöppel, Stefan; Maeder, Philippe; Meuli, Reto; Krueger, Gunnar

2014-01-01

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease. PMID:25429357

Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.

PubMed

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.

Orientation selectivity based structure for texture classification

NASA Astrophysics Data System (ADS)

Wu, Jinjian; Lin, Weisi; Shi, Guangming; Zhang, Yazhong; Lu, Liu

2014-10-01

Local structure, e.g., local binary pattern (LBP), is widely used in texture classification. However, LBP is too sensitive to disturbance. In this paper, we introduce a novel structure for texture classification. Researches on cognitive neuroscience indicate that the primary visual cortex presents remarkable orientation selectivity for visual information extraction. Inspired by this, we investigate the orientation similarities among neighbor pixels, and propose an orientation selectivity based pattern for local structure description. Experimental results on texture classification demonstrate that the proposed structure descriptor is quite robust to disturbance.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Vulnerable land ecosystems classification using spatial context and spectral indices

NASA Astrophysics Data System (ADS)

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

2017-10-01

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

Evaluation of different classification methods for the diagnosis of schizophrenia based on functional near-infrared spectroscopy.

PubMed

Li, Zhaohua; Wang, Yuduo; Quan, Wenxiang; Wu, Tongning; Lv, Bin

2015-02-15

Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population. In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods. We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier. This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals. Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel method to guide classification of para swimmers with limb deficiency.

PubMed

Hogarth, Luke; Payton, Carl; Van de Vliet, Peter; Connick, Mark; Burkett, Brendan

2018-05-30

The International Paralympic Committee has directed International Federations that govern Para sports to develop evidence-based classification systems. This study defined the impact of limb deficiency impairment on 100 m freestyle performance to guide an evidence-based classification system in Para Swimming, which will be implemented following the 2020 Tokyo Paralympic games. Impairment data and competitive race performances of 90 international swimmers with limb deficiency were collected. Ensemble partial least squares regression established the relationship between relative limb length measures and competitive 100 m freestyle performance. The model explained 80% of the variance in 100 m freestyle performance, and found hand length and forearm length to be the most important predictors of performance. Based on the results of this model, Para swimmers were clustered into four-, five-, six- and seven-class structures using nonparametric kernel density estimations. The validity of these classification structures, and effectiveness against the current classification system, were examined by establishing within-class variations in 100 m freestyle performance and differences between adjacent classes. The derived classification structures were found to be more effective than current classification based on these criteria. This study provides a novel method that can be used to improve the objectivity and transparency of decision-making in Para sport classification. Expert consensus from experienced coaches, Para swimmers, classifiers and sport science and medicine personnel will benefit the translation of these findings into a revised classification system that is accepted by the Para swimming community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Classifying diseases and remedies in ethnomedicine and ethnopharmacology.

PubMed

Staub, Peter O; Geck, Matthias S; Weckerle, Caroline S; Casu, Laura; Leonti, Marco

2015-11-04

Ethnopharmacology focuses on the understanding of local and indigenous use of medicines and therefore an emic approach is inevitable. Often, however, standard biomedical disease classifications are used to describe and analyse local diseases and remedies. Standard classifications might be a valid tool for cross-cultural comparisons and bioprospecting purposes but are not suitable to understand the local perception of disease and use of remedies. Different standard disease classification systems exist but their suitability for cross-cultural comparisons of ethnomedical data has never been assessed. Depending on the research focus, (I) ethnomedical, (II) cross-cultural, and (III) bioprospecting, we provide suggestions for the use of specific classification systems. We analyse three different standard biomedical classification systems (the International Classification of Diseases (ICD); the Economic Botany Data Collection Standard (EBDCS); and the International Classification of Primary Care (ICPC)), and discuss their value for categorizing diseases of ethnomedical systems and their suitability for cross-cultural research in ethnopharmacology. Moreover, based on the biomedical uses of all approved plant derived biomedical drugs, we propose a biomedical therapy-based classification system as a guide for the discovery of drugs from ethnopharmacological sources. Widely used standards, such as the International Classification of Diseases (ICD) by the WHO and the Economic Botany Data Collection Standard (EBDCS) are either technically challenging due to a categorisation system based on clinical examinations, which are usually not possible during field research (ICD) or lack clear biomedical criteria combining disorders and medical effects in an imprecise and confusing way (EBDCS). The International Classification of Primary Care (ICPC), also accepted by the WHO, has more in common with ethnomedical reality than the ICD or the EBDCS, as the categories are designed according to patient's perceptions and are less influenced by clinical medicine. Since diagnostic tools are not required, medical ethnobotanists and ethnopharmacologists can easily classify reported symptoms and complaints with the ICPC in one of the "chapters" based on 17 body systems, psychological and social problems. Also the biomedical uses of plant-derived drugs are classifiable into 17 broad organ- and therapy-based use-categories but can easily be divided into more specific subcategories. Depending on the research focus (I-III) we propose the following classification systems: I. Ethnomedicine: Ethnomedicine is culture-bound and local classifications have to be understood from an emic perspective. Consequently, the application of prefabricated, "one-size fits all" biomedical classification schemes is of limited value. II. Cross-cultural analysis: The ICPC is a suitable standard that can be applied but modified as required. III. Bioprospecting: We suggest a biomedical therapy-driven classification system with currently 17 use-categories based on biomedical uses of all approved plant derived natural product drugs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Tissue classification for laparoscopic image understanding based on multispectral texture analysis

NASA Astrophysics Data System (ADS)

Zhang, Yan; Wirkert, Sebastian J.; Iszatt, Justin; Kenngott, Hannes; Wagner, Martin; Mayer, Benjamin; Stock, Christian; Clancy, Neil T.; Elson, Daniel S.; Maier-Hein, Lena

2016-03-01

Intra-operative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study we show (1) that multispectral imaging data is superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) that combining the tissue texture with the reflectance spectrum improves the classification performance. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on the rating applicable to the freight classification description published in the National Motor...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

A System for Supporting Development and Update of the International Classification of Health Interventions (ICHI).

PubMed

Donada, Marc; Della Mea, Vincenzo; Cumerlato, Megan; Rankin, Nicole; Madden, Richard

2018-01-01

The International Classification of Health Interventions (ICHI) is a member of the WHO Family of International Classifications, being developed to provide a common tool for reporting and analysing health interventions for statistical purposes. A web-based platform for classification development and update has been specifically developed to support the initial development step and then, after final approval, the continuous revision and update of the classification. The platform provides features for classification editing, versioning, comment management and URI identifiers. During the last 12 months it has been used for developing the ICHI Beta version, replacing the previous process based on the exchange of Excel files. At November 2017, 90 users have provided input to the development of the classification, which has resulted in 2913 comments and 2971 changes in the classification, since June 2017. Further work includes the development of an URI API for machine to machine communication, following the model established for ICD-11.

Drug related webpages classification using images and text information based on multi-kernel learning

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Xiao, Liping; Zheng, Wenjuan

2015-12-01

In this paper, multi-kernel learning(MKL) is used for drug-related webpages classification. First, body text and image-label text are extracted through HTML parsing, and valid images are chosen by the FOCARSS algorithm. Second, text based BOW model is used to generate text representation, and image-based BOW model is used to generate images representation. Last, text and images representation are fused with a few methods. Experimental results demonstrate that the classification accuracy of MKL is higher than those of all other fusion methods in decision level and feature level, and much higher than the accuracy of single-modal classification.

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

Selecting reusable components using algebraic specifications

NASA Technical Reports Server (NTRS)

Eichmann, David A.

1992-01-01

A significant hurdle confronts the software reuser attempting to select candidate components from a software repository - discriminating between those components without resorting to inspection of the implementation(s). We outline a mixed classification/axiomatic approach to this problem based upon our lattice-based faceted classification technique and Guttag and Horning's algebraic specification techniques. This approach selects candidates by natural language-derived classification, by their interfaces, using signatures, and by their behavior, using axioms. We briefly outline our problem domain and related work. Lattice-based faceted classifications are described; the reader is referred to surveys of the extensive literature for algebraic specification techniques. Behavioral support for reuse queries is presented, followed by the conclusions.

Semi-supervised classification tool for DubaiSat-2 multispectral imagery

NASA Astrophysics Data System (ADS)

Al-Mansoori, Saeed

2015-10-01

This paper addresses a semi-supervised classification tool based on a pixel-based approach of the multi-spectral satellite imagery. There are not many studies demonstrating such algorithm for the multispectral images, especially when the image consists of 4 bands (Red, Green, Blue and Near Infrared) as in DubaiSat-2 satellite images. The proposed approach utilizes both unsupervised and supervised classification schemes sequentially to identify four classes in the image, namely, water bodies, vegetation, land (developed and undeveloped areas) and paved areas (i.e. roads). The unsupervised classification concept is applied to identify two classes; water bodies and vegetation, based on a well-known index that uses the distinct wavelengths of visible and near-infrared sunlight that is absorbed and reflected by the plants to identify the classes; this index parameter is called "Normalized Difference Vegetation Index (NDVI)". Afterward, the supervised classification is performed by selecting training homogenous samples for roads and land areas. Here, a precise selection of training samples plays a vital role in the classification accuracy. Post classification is finally performed to enhance the classification accuracy, where the classified image is sieved, clumped and filtered before producing final output. Overall, the supervised classification approach produced higher accuracy than the unsupervised method. This paper shows some current preliminary research results which point out the effectiveness of the proposed technique in a virtual perspective.

[Evaluation of traditional pathological classification at molecular classification era for gastric cancer].

PubMed

Yu, Yingyan

2014-01-01

Histopathological classification is in a pivotal position in both basic research and clinical diagnosis and treatment of gastric cancer. Currently, there are different classification systems in basic science and clinical application. In medical literatures, different classifications are used including Lauren and WHO systems, which have confused many researchers. Lauren classification has been proposed for half a century, but is still used worldwide. It shows many advantages of simple, easy handling with prognostic significance. The WHO classification scheme is better than Lauren classification in that it is continuously being revised according to the progress of gastric cancer, and is always used in the clinical and pathological diagnosis of common scenarios. Along with the progression of genomics, transcriptomics, proteomics, metabolomics researches, molecular classification of gastric cancer becomes the current hot topics. The traditional therapeutic approach based on phenotypic characteristics of gastric cancer will most likely be replaced with a gene variation mode. The gene-targeted therapy against the same molecular variation seems more reasonable than traditional chemical treatment based on the same morphological change.

Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

PubMed

Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

2017-06-01

Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

Chinese Sentence Classification Based on Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Gu, Chengwei; Wu, Ming; Zhang, Chuang

2017-10-01

Sentence classification is one of the significant issues in Natural Language Processing (NLP). Feature extraction is often regarded as the key point for natural language processing. Traditional ways based on machine learning can not take high level features into consideration, such as Naive Bayesian Model. The neural network for sentence classification can make use of contextual information to achieve greater results in sentence classification tasks. In this paper, we focus on classifying Chinese sentences. And the most important is that we post a novel architecture of Convolutional Neural Network (CNN) to apply on Chinese sentence classification. In particular, most of the previous methods often use softmax classifier for prediction, we embed a linear support vector machine to substitute softmax in the deep neural network model, minimizing a margin-based loss to get a better result. And we use tanh as an activation function, instead of ReLU. The CNN model improve the result of Chinese sentence classification tasks. Experimental results on the Chinese news title database validate the effectiveness of our model.

Abstracting of suspected illegal land use in urban areas using case-based classification of remote sensing images

NASA Astrophysics Data System (ADS)

Chen, Fulong; Wang, Chao; Yang, Chengyun; Zhang, Hong; Wu, Fan; Lin, Wenjuan; Zhang, Bo

2008-11-01

This paper proposed a method that uses a case-based classification of remote sensing images and applied this method to abstract the information of suspected illegal land use in urban areas. Because of the discrete cases for imagery classification, the proposed method dealt with the oscillation of spectrum or backscatter within the same land use category, and it not only overcame the deficiency of maximum likelihood classification (the prior probability of land use could not be obtained) but also inherited the advantages of the knowledge-based classification system, such as artificial intelligence and automatic characteristics. Consequently, the proposed method could do the classifying better. Then the researchers used the object-oriented technique for shadow removal in highly dense city zones. With multi-temporal SPOT 5 images whose resolution was 2.5×2.5 meters, the researchers found that the method can abstract suspected illegal land use information in urban areas using post-classification comparison technique.

Image Analysis and Classification Based on Soil Strength

DTIC Science & Technology

2016-08-01

Satellite imagery classification is useful for a variety of commonly used ap- plications, such as land use classification, agriculture , wetland...required use of a coinci- dent digital elevation model (DEM) and a high-resolution orthophoto- graph collected by the National Agriculture Imagery Program...14. ABSTRACT Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture

Inter-comparison of weather and circulation type classifications for hydrological drought development

NASA Astrophysics Data System (ADS)

Fleig, Anne K.; Tallaksen, Lena M.; Hisdal, Hege; Stahl, Kerstin; Hannah, David M.

Classifications of weather and circulation patterns are often applied in research seeking to relate atmospheric state to surface environmental phenomena. However, numerous procedures have been applied to define the patterns, thus limiting comparability between studies. The COST733 Action “ Harmonisation and Applications of Weather Type Classifications for European regions” tests 73 different weather type classifications (WTC) and their associate weather types (WTs) and compares the WTCs’ utility for various applications. The objective of this study is to evaluate the potential of these WTCs for analysis of regional hydrological drought development in north-western Europe. Hydrological drought is defined in terms of a Regional Drought Area Index (RDAI), which is based on deficits derived from daily river flow series. RDAI series (1964-2001) were calculated for four homogeneous regions in Great Britain and two in Denmark. For each region, WTs associated with hydrological drought development were identified based on antecedent and concurrent WT-frequencies for major drought events. The utility of the different WTCs for the study of hydrological drought development was evaluated, and the influence of WTC attributes, i.e. input variables, number of defined WTs and general classification concept, on WTC performance was assessed. The objective Grosswetterlagen (OGWL), the objective Second-Generation Lamb Weather Type Classification (LWT2) with 18 WTs and two implementations of the objective Wetterlagenklassifikation (WLK; with 40 and 28 WTs) outperformed all other WTCs. In general, WTCs with more WTs (⩾27) were found to perform better than WTCs with less (⩽18) WTs. The influence of input variables was not consistent across the different classification procedures, and the performance of a WTC was determined primarily by the classification procedure itself. Overall, classification procedures following the relatively simple general classification concept of predefining WTs based on thresholds, performed better than those based on more sophisticated classification concepts such as deriving WTs by cluster analysis or artificial neural networks. In particular, PCA based WTCs with 9 WTs and automated WTCs with a high number of predefined WTs (subjectively and threshold based) performed well. It is suggested that the explicit consideration of the air flow characteristics of meridionality, zonality and cyclonicity in the definition of WTs is a useful feature for a WTC when analysing regional hydrological drought development.

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2012 CFR

2012-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2013 CFR

2013-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2010 CFR

2010-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2014 CFR

2014-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2011 CFR

2011-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer

PubMed Central

Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results. PMID:28467468

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer.

PubMed

Rogiers, Bart; Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results.

Limitations and implications of stream classification

USGS Publications Warehouse

Juracek, K.E.; Fitzpatrick, F.A.

2003-01-01

Stream classifications that are based on channel form, such as the Rosgen Level II classification, are useful tools for the physical description and grouping of streams and for providing a means of communication for stream studies involving scientists and (or) managers with different backgrounds. The Level II classification also is used as a tool to assess stream stability, infer geomorphic processes, predict future geomorphic response, and guide stream restoration or rehabilitation activities. The use of the Level II classification for these additional purposes is evaluated in this paper. Several examples are described to illustrate the limitations and management implications of the Level II classification. Limitations include: (1) time dependence, (2) uncertain applicability across physical environments, (3) difficulty in identification of a true equilibrium condition, (4) potential for incorrect determination of bankfull elevation, and (5) uncertain process significance of classification criteria. Implications of using stream classifications based on channel form, such as Rosgen's, include: (1) acceptance of the limitations, (2) acceptance of the risk of classifying streams incorrectly, and (3) classification results may be used inappropriately. It is concluded that use of the Level II classification for purposes beyond description and communication is not appropriate. Research needs are identified that, if addressed, may help improve the usefulness of the Level II classification.

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

Computer-aided classification of optical images for diagnosis of osteoarthritis in the finger joints.

PubMed

Zhang, Jiang; Wang, James Z; Yuan, Zhen; Sobel, Eric S; Jiang, Huabei

2011-01-01

This study presents a computer-aided classification method to distinguish osteoarthritis finger joints from healthy ones based on the functional images captured by x-ray guided diffuse optical tomography. Three imaging features, joint space width, optical absorption, and scattering coefficients, are employed to train a Least Squares Support Vector Machine (LS-SVM) classifier for osteoarthritis classification. The 10-fold validation results show that all osteoarthritis joints are clearly identified and all healthy joints are ruled out by the LS-SVM classifier. The best sensitivity, specificity, and overall accuracy of the classification by experienced technicians based on manual calculation of optical properties and visual examination of optical images are only 85%, 93%, and 90%, respectively. Therefore, our LS-SVM based computer-aided classification is a considerably improved method for osteoarthritis diagnosis.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2016-04-01

When assessing hydrogeological conditions at the regional scale, the analyst is often confronted with uncertainty of structures, inputs and processes while having to base inference on scarce and patchy data. Haaf and Barthel (2015) proposed a concept for handling this predicament by developing a groundwater systems classification framework, where information is transferred from similar, but well-explored and better understood to poorly described systems. The concept is based on the central hypothesis that similar systems react similarly to the same inputs and vice versa. It is conceptually related to PUB (Prediction in ungauged basins) where organization of systems and processes by quantitative methods is intended and used to improve understanding and prediction. Furthermore, using the framework it is expected that regional conceptual and numerical models can be checked or enriched by ensemble generated data from neighborhood-based estimators. In a first step, groundwater hydrographs from a large dataset in Southern Germany are compared in an effort to identify structural similarity in groundwater dynamics. A number of approaches to group hydrographs, mostly based on a similarity measure - which have previously only been used in local-scale studies, can be found in the literature. These are tested alongside different global feature extraction techniques. The resulting classifications are then compared to a visual "expert assessment"-based classification which serves as a reference. A ranking of the classification methods is carried out and differences shown. Selected groups from the classifications are related to geological descriptors. Here we present the most promising results from a comparison of classifications based on series correlation, different series distances and series features, such as the coefficients of the discrete Fourier transform and the intrinsic mode functions of empirical mode decomposition. Additionally, we show examples of classes corresponding to geological descriptors. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria.

Resolution in forensic microbial genotyping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Velsko, S P

2005-08-30

Resolution is a key parameter for differentiating among the large number of strain typing methods that could be applied to pathogens involved in bioterror events or biocrimes. In this report we develop a first-principles analysis of strain typing resolution using a simple mathematical model to provide a basis for the rational design of microbial typing systems for forensic applications. We derive two figures of merit that describe the resolving power and phylogenetic depth of a strain typing system. Rough estimates of these figures-of-merit for MLVA, MLST, IS element, AFLP, hybridization microarrays, and other bacterial typing methods are derived from mutationmore » rate data reported in the literature. We also discuss the general problem of how to construct a ''universal'' practical typing system that has the highest possible resolution short of whole-genome sequencing, and that is applicable with minimal modification to a wide range of pathogens.« less

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

Classification and Quality Evaluation of Tobacco Leaves Based on Image Processing and Fuzzy Comprehensive Evaluation

PubMed Central

Zhang, Fan; Zhang, Xinhong

2011-01-01

Most of classification, quality evaluation or grading of the flue-cured tobacco leaves are manually operated, which relies on the judgmental experience of experts, and inevitably limited by personal, physical and environmental factors. The classification and the quality evaluation are therefore subjective and experientially based. In this paper, an automatic classification method of tobacco leaves based on the digital image processing and the fuzzy sets theory is presented. A grading system based on image processing techniques was developed for automatically inspecting and grading flue-cured tobacco leaves. This system uses machine vision for the extraction and analysis of color, size, shape and surface texture. Fuzzy comprehensive evaluation provides a high level of confidence in decision making based on the fuzzy logic. The neural network is used to estimate and forecast the membership function of the features of tobacco leaves in the fuzzy sets. The experimental results of the two-level fuzzy comprehensive evaluation (FCE) show that the accuracy rate of classification is about 94% for the trained tobacco leaves, and the accuracy rate of the non-trained tobacco leaves is about 72%. We believe that the fuzzy comprehensive evaluation is a viable way for the automatic classification and quality evaluation of the tobacco leaves. PMID:22163744

Hierarchical trie packet classification algorithm based on expectation-maximization clustering.

PubMed

Bi, Xia-An; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm.

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data

NASA Astrophysics Data System (ADS)

Gajda, Agnieszka; Wójtowicz-Nowakowska, Anna

2013-04-01

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data Land cover maps are generally produced on the basis of high resolution imagery. Recently, LiDAR (Light Detection and Ranging) data have been brought into use in diverse applications including land cover mapping. In this study we attempted to assess the accuracy of land cover classification using both high resolution aerial imagery and LiDAR data (airborne laser scanning, ALS), testing two classification approaches: a pixel-based classification and object-oriented image analysis (OBIA). The study was conducted on three test areas (3 km2 each) in the administrative area of Kraków, Poland, along the course of the Vistula River. They represent three different dominating land cover types of the Vistula River valley. Test site 1 had a semi-natural vegetation, with riparian forests and shrubs, test site 2 represented a densely built-up area, and test site 3 was an industrial site. Point clouds from ALS and ortophotomaps were both captured in November 2007. Point cloud density was on average 16 pt/m2 and it contained additional information about intensity and encoded RGB values. Ortophotomaps had a spatial resolution of 10 cm. From point clouds two raster maps were generated: intensity (1) and (2) normalised Digital Surface Model (nDSM), both with the spatial resolution of 50 cm. To classify the aerial data, a supervised classification approach was selected. Pixel based classification was carried out in ERDAS Imagine software. Ortophotomaps and intensity and nDSM rasters were used in classification. 15 homogenous training areas representing each cover class were chosen. Classified pixels were clumped to avoid salt and pepper effect. Object oriented image object classification was carried out in eCognition software, which implements both the optical and ALS data. Elevation layers (intensity, firs/last reflection, etc.) were used at segmentation stage due to proper wages usage. Thus a more precise and unambiguous boundaries of segments (objects) were received. As a results of the classification 5 classes of land cover (buildings, water, high and low vegetation and others) were extracted. Both pixel-based image analysis and OBIA were conducted with a minimum mapping unit of 10m2. Results were validated on the basis on manual classification and random points (80 per test area), reference data set was manually interpreted using ortophotomaps and expert knowledge of the test site areas.

The Extension of Holland's Occupational Classification to All Occupations in the Dictionary of Occupational Titles.

ERIC Educational Resources Information Center

Viernstein, Mary Cowan

Two methods are presented for extending Holland's occupational classification to include all occupations in the Dictionary of Occupational Titles (DOT). Holland's classification is based on a theory of personality types, with occupations in the classification organized into major categories (Realistic, Investigative, Artistic, Social,…

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

NASA Astrophysics Data System (ADS)

Hamedianfar, Alireza; Shafri, Helmi Zulhaidi Mohd

2016-04-01

This paper integrates decision tree-based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.

SB certification handout material requirements, test methods, responsibilities, and minimum classification levels for mixture-based specification for flexible base.

DOT National Transportation Integrated Search

2012-10-01

A handout with tables representing the material requirements, test methods, responsibilities, and minimum classification levels mixture-based specification for flexible base and details on aggregate and test methods employed, along with agency and co...

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

NASA Technical Reports Server (NTRS)

Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

2012-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

PubMed

Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

2018-05-16

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2000-12-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Meeting the criteria of a nursing diagnosis classification: Evaluation of ICNP, ICF, NANDA and ZEFP.

PubMed

Müller-Staub, Maria; Lavin, Mary Ann; Needham, Ian; van Achterberg, Theo

2007-07-01

Few studies described nursing diagnosis classification criteria and how classifications meet these criteria. The purpose was to identify criteria for nursing diagnosis classifications and to assess how these criteria are met by different classifications. First, a literature review was conducted (N=50) to identify criteria for nursing diagnoses classifications and to evaluate how these criteria are met by the International Classification of Nursing Practice (ICNP), the International Classification of Functioning, Disability and Health (ICF), the International Nursing Diagnoses Classification (NANDA), and the Nursing Diagnostic System of the Centre for Nursing Development and Research (ZEFP). Using literature review based general and specific criteria, the principal investigator evaluated each classification, applying a matrix. Second, a convenience sample of 20 nursing experts from different Swiss care institutions answered standardized interview forms, querying current national and international classification state and use. The first general criterion is that a diagnosis classification should describe the knowledge base and subject matter for which the nursing profession is responsible. ICNP) and NANDA meet this goal. The second general criterion is that each class fits within a central concept. The ICF and NANDA are the only two classifications built on conceptually driven classes. The third general classification criterion is that each diagnosis possesses a description, diagnostic criteria, and related etiologies. Although ICF and ICNP describe diagnostic terms, only NANDA fulfils this criterion. The analysis indicated that NANDA fulfilled most of the specific classification criteria in the matrix. The nursing experts considered NANDA to be the best-researched and most widely implemented classification in Switzerland and internationally. The international literature and the opinion of Swiss expert nurses indicate that-from the perspective of classifying comprehensive nursing diagnoses-NANDA should be recommended for nursing practice and electronic nursing documentation. Study limitations and future research needs are discussed.

How should children with speech sound disorders be classified? A review and critical evaluation of current classification systems.

PubMed

Waring, R; Knight, R

2013-01-01

Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of theoretically differing classification systems have been proposed based on either an aetiological (medical) approach, a descriptive-linguistic approach or a processing approach. To describe and review the supporting evidence, and to provide a critical evaluation of the current childhood SSD classification systems. Descriptions of the major specific approaches to classification are reviewed and research papers supporting the reliability and validity of the systems are evaluated. Three specific paediatric SSD classification systems; the aetiologic-based Speech Disorders Classification System, the descriptive-linguistic Differential Diagnosis system, and the processing-based Psycholinguistic Framework are identified as potentially useful in classifying children with SSD into homogeneous subgroups. The Differential Diagnosis system has a growing body of empirical support from clinical population studies, across language error pattern studies and treatment efficacy studies. The Speech Disorders Classification System is currently a research tool with eight proposed subgroups. The Psycholinguistic Framework is a potential bridge to linking cause and surface level speech errors. There is a need for a universally agreed-upon classification system that is useful to clinicians and researchers. The resulting classification system needs to be robust, reliable and valid. A universal classification system would allow for improved tailoring of treatments to subgroups of SSD which may, in turn, lead to improved treatment efficacy. © 2012 Royal College of Speech and Language Therapists.

A classification model of Hyperion image base on SAM combined decision tree

NASA Astrophysics Data System (ADS)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.

Plant species classification using flower images—A comparative study of local feature representations

PubMed Central

Seeland, Marco; Rzanny, Michael; Alaqraa, Nedal; Wäldchen, Jana; Mäder, Patrick

2017-01-01

Steady improvements of image description methods induced a growing interest in image-based plant species classification, a task vital to the study of biodiversity and ecological sensitivity. Various techniques have been proposed for general object classification over the past years and several of them have already been studied for plant species classification. However, results of these studies are selective in the evaluated steps of a classification pipeline, in the utilized datasets for evaluation, and in the compared baseline methods. No study is available that evaluates the main competing methods for building an image representation on the same datasets allowing for generalized findings regarding flower-based plant species classification. The aim of this paper is to comparatively evaluate methods, method combinations, and their parameters towards classification accuracy. The investigated methods span from detection, extraction, fusion, pooling, to encoding of local features for quantifying shape and color information of flower images. We selected the flower image datasets Oxford Flower 17 and Oxford Flower 102 as well as our own Jena Flower 30 dataset for our experiments. Findings show large differences among the various studied techniques and that their wisely chosen orchestration allows for high accuracies in species classification. We further found that true local feature detectors in combination with advanced encoding methods yield higher classification results at lower computational costs compared to commonly used dense sampling and spatial pooling methods. Color was found to be an indispensable feature for high classification results, especially while preserving spatial correspondence to gray-level features. In result, our study provides a comprehensive overview of competing techniques and the implications of their main parameters for flower-based plant species classification. PMID:28234999

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Mycofier: a new machine learning-based classifier for fungal ITS sequences.

PubMed

Delgado-Serrano, Luisa; Restrepo, Silvia; Bustos, Jose Ricardo; Zambrano, Maria Mercedes; Anzola, Juan Manuel

2016-08-11

The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

PubMed

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

2008-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

2009-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

Assessment of land use and land cover change using spatiotemporal analysis of landscape: case study in south of Tehran.

PubMed

Sabr, Abutaleb; Moeinaddini, Mazaher; Azarnivand, Hossein; Guinot, Benjamin

2016-12-01

In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.

a Two-Step Classification Approach to Distinguishing Similar Objects in Mobile LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

He, H.; Khoshelham, K.; Fraser, C.

2017-09-01

Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

A hybrid sensing approach for pure and adulterated honey classification.

PubMed

Subari, Norazian; Mohamad Saleh, Junita; Md Shakaff, Ali Yeon; Zakaria, Ammar

2012-10-17

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

A discrete wavelet based feature extraction and hybrid classification technique for microarray data analysis.

PubMed

Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan

2014-01-01

Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

Property Specification Patterns for intelligence building software

NASA Astrophysics Data System (ADS)

Chun, Seungsu

2018-03-01

In this paper, through the property specification pattern research for Modal MU(μ) logical aspects present a single framework based on the pattern of intelligence building software. In this study, broken down by state property specification pattern classification of Dwyer (S) and action (A) and was subdivided into it again strong (A) and weaknesses (E). Through these means based on a hierarchical pattern classification of the property specification pattern analysis of logical aspects Mu(μ) was applied to the pattern classification of the examples used in the actual model checker. As a result, not only can a more accurate classification than the existing classification systems were easy to create and understand the attributes specified.

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Accurate crop classification using hierarchical genetic fuzzy rule-based systems

NASA Astrophysics Data System (ADS)

Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

2014-10-01

This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

PubMed

Deschamps, Kevin; Matricali, Giovanni Arnoldo; Desmet, Dirk; Roosen, Philip; Keijsers, Noel; Nobels, Frank; Bruyninckx, Herman; Staes, Filip

2016-09-01

The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making. Copyright © 2016 Elsevier B.V. All rights reserved.

A comparative study for chest radiograph image retrieval using binary texture and deep learning classification.

PubMed

Anavi, Yaron; Kogan, Ilya; Gelbart, Elad; Geva, Ofer; Greenspan, Hayit

2015-08-01

In this work various approaches are investigated for X-ray image retrieval and specifically chest pathology retrieval. Given a query image taken from a data set of 443 images, the objective is to rank images according to similarity. Different features, including binary features, texture features, and deep learning (CNN) features are examined. In addition, two approaches are investigated for the retrieval task. One approach is based on the distance of image descriptors using the above features (hereon termed the "descriptor"-based approach); the second approach ("classification"-based approach) is based on a probability descriptor, generated by a pair-wise classification of each two classes (pathologies) and their decision values using an SVM classifier. Best results are achieved using deep learning features in a classification scheme.

New insights into the classification and nomenclature of cortical GABAergic interneurons.

PubMed

DeFelipe, Javier; López-Cruz, Pedro L; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R; Huang, Josh; Jones, Edward G; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A; Marín, Oscar; Markram, Henry; McBain, Chris J; Meyer, Hanno S; Monyer, Hannah; Nelson, Sacha B; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L R; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M; Sherwood, Chet C; Staiger, Jochen F; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A

2013-03-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

New insights into the classification and nomenclature of cortical GABAergic interneurons

PubMed Central

DeFelipe, Javier; López-Cruz, Pedro L.; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F.; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R.; Huang, Josh; Jones, Edward G.; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A.; Marín, Oscar; Markram, Henry; McBain, Chris J.; Meyer, Hanno S.; Monyer, Hannah; Nelson, Sacha B.; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L. R.; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M.; Sherwood, Chet C.; Staiger, Jochen F.; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A.

2013-01-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts’ assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus. PMID:23385869

Automatic topic identification of health-related messages in online health community using text classification.

PubMed

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

An unbalanced spectra classification method based on entropy

NASA Astrophysics Data System (ADS)

Liu, Zhong-bao; Zhao, Wen-juan

2017-05-01

How to solve the problem of distinguishing the minority spectra from the majority of the spectra is quite important in astronomy. In view of this, an unbalanced spectra classification method based on entropy (USCM) is proposed in this paper to deal with the unbalanced spectra classification problem. USCM greatly improves the performances of the traditional classifiers on distinguishing the minority spectra as it takes the data distribution into consideration in the process of classification. However, its time complexity is exponential with the training size, and therefore, it can only deal with the problem of small- and medium-scale classification. How to solve the large-scale classification problem is quite important to USCM. It can be easily obtained by mathematical computation that the dual form of USCM is equivalent to the minimum enclosing ball (MEB), and core vector machine (CVM) is introduced, USCM based on CVM is proposed to deal with the large-scale classification problem. Several comparative experiments on the 4 subclasses of K-type spectra, 3 subclasses of F-type spectra and 3 subclasses of G-type spectra from Sloan Digital Sky Survey (SDSS) verify USCM and USCM based on CVM perform better than kNN (k nearest neighbor) and SVM (support vector machine) in dealing with the problem of rare spectra mining respectively on the small- and medium-scale datasets and the large-scale datasets.

The addition of entropy-based regularity parameters improves sleep stage classification based on heart rate variability.

PubMed

Aktaruzzaman, M; Migliorini, M; Tenhunen, M; Himanen, S L; Bianchi, A M; Sassi, R

2015-05-01

The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens's Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.

Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people

NASA Astrophysics Data System (ADS)

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Fengkui; Liu, Feixiang

2017-09-01

Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface (BCI) has shown its effectiveness for the control of rehabilitation devices designed for large body parts of the patients with neurologic impairments. In order to validate the feasibility of using EEG to decode the MI of a single index finger and constructing a BCI-enhanced finger rehabilitation system, we collected EEG data during right hand index finger MI and rest state for five healthy subjects and proposed a pattern recognition approach for classifying these two mental states. First, Fisher's linear discriminant criteria and power spectral density analysis were used to analyze the event-related desynchronization patterns. Second, both band power and approximate entropy were extracted as features. Third, aiming to eliminate the abnormal samples in the dictionary and improve the classification performance of the conventional sparse representation-based classification (SRC) method, we proposed a novel dictionary cleaned sparse representation-based classification (DCSRC) method for final classification. The experimental results show that the proposed DCSRC method gives better classification accuracies than SRC and an average classification accuracy of 81.32% is obtained for five subjects. Thus, it is demonstrated that single right hand index finger MI can be decoded from the sensorimotor rhythms, and the feature patterns of index finger MI and rest state can be well recognized for robotic exoskeleton initiation.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

Unveiling a spinor field classification with non-Abelian gauge symmetries

NASA Astrophysics Data System (ADS)

Fabbri, Luca; da Rocha, Roldão

2018-05-01

A spinor fields classification with non-Abelian gauge symmetries is introduced, generalizing the U(1) gauge symmetries-based Lounesto's classification. Here, a more general classification, contrary to the Lounesto's one, encompasses spinor multiplets, corresponding to non-Abelian gauge fields. The particular case of SU(2) gauge symmetry, encompassing electroweak and electromagnetic conserved charges, is then implemented by a non-Abelian spinor classification, now involving 14 mixed classes of spinor doublets. A richer flagpole, dipole, and flag-dipole structure naturally descends from this general classification. The Lounesto's classification of spinors is shown to arise as a Pauli's singlet, into this more general classification.

Multi-material classification of dry recyclables from municipal solid waste based on thermal imaging.

PubMed

Gundupalli, Sathish Paulraj; Hait, Subrata; Thakur, Atul

2017-12-01

There has been a significant rise in municipal solid waste (MSW) generation in the last few decades due to rapid urbanization and industrialization. Due to the lack of source segregation practice, a need for automated segregation of recyclables from MSW exists in the developing countries. This paper reports a thermal imaging based system for classifying useful recyclables from simulated MSW sample. Experimental results have demonstrated the possibility to use thermal imaging technique for classification and a robotic system for sorting of recyclables in a single process step. The reported classification system yields an accuracy in the range of 85-96% and is comparable with the existing single-material recyclable classification techniques. We believe that the reported thermal imaging based system can emerge as a viable and inexpensive large-scale classification-cum-sorting technology in recycling plants for processing MSW in developing countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

[The establishment, development and application of classification approach of freshwater phytoplankton based on the functional group: a review].

PubMed

Yang, Wen; Zhu, Jin-Yong; Lu, Kai-Hong; Wan, Li; Mao, Xiao-Hua

2014-06-01

Appropriate schemes for classification of freshwater phytoplankton are prerequisites and important tools for revealing phytoplanktonic succession and studying freshwater ecosystems. An alternative approach, functional group of freshwater phytoplankton, has been proposed and developed due to the deficiencies of Linnaean and molecular identification in ecological applications. The functional group of phytoplankton is a classification scheme based on autoecology. In this study, the theoretical basis and classification criterion of functional group (FG), morpho-functional group (MFG) and morphology-based functional group (MBFG) were summarized, as well as their merits and demerits. FG was considered as the optimal classification approach for the aquatic ecology research and aquatic environment evaluation. The application status of FG was introduced, with the evaluation standards and problems of two approaches to assess water quality on the basis of FG, index methods of Q and QR, being briefly discussed.

Classification-Based Spatial Error Concealment for Visual Communications

NASA Astrophysics Data System (ADS)

Chen, Meng; Zheng, Yefeng; Wu, Min

2006-12-01

In an error-prone transmission environment, error concealment is an effective technique to reconstruct the damaged visual content. Due to large variations of image characteristics, different concealment approaches are necessary to accommodate the different nature of the lost image content. In this paper, we address this issue and propose using classification to integrate the state-of-the-art error concealment techniques. The proposed approach takes advantage of multiple concealment algorithms and adaptively selects the suitable algorithm for each damaged image area. With growing awareness that the design of sender and receiver systems should be jointly considered for efficient and reliable multimedia communications, we proposed a set of classification-based block concealment schemes, including receiver-side classification, sender-side attachment, and sender-side embedding. Our experimental results provide extensive performance comparisons and demonstrate that the proposed classification-based error concealment approaches outperform the conventional approaches.

Uav-Based Crops Classification with Joint Features from Orthoimage and Dsm Data

NASA Astrophysics Data System (ADS)

Liu, B.; Shi, Y.; Duan, Y.; Wu, W.

2018-04-01

Accurate crops classification remains a challenging task due to the same crop with different spectra and different crops with same spectrum phenomenon. Recently, UAV-based remote sensing approach gains popularity not only for its high spatial and temporal resolution, but also for its ability to obtain spectraand spatial data at the same time. This paper focus on how to take full advantages of spatial and spectrum features to improve crops classification accuracy, based on an UAV platform equipped with a general digital camera. Texture and spatial features extracted from the RGB orthoimage and the digital surface model of the monitoring area are analysed and integrated within a SVM classification framework. Extensive experiences results indicate that the overall classification accuracy is drastically improved from 72.9 % to 94.5 % when the spatial features are combined together, which verified the feasibility and effectiveness of the proposed method.

A Characteristics-Based Approach to Radioactive Waste Classification in Advanced Nuclear Fuel Cycles

NASA Astrophysics Data System (ADS)

Djokic, Denia

The radioactive waste classification system currently used in the United States primarily relies on a source-based framework. This has lead to numerous issues, such as wastes that are not categorized by their intrinsic risk, or wastes that do not fall under a category within the framework and therefore are without a legal imperative for responsible management. Furthermore, in the possible case that advanced fuel cycles were to be deployed in the United States, the shortcomings of the source-based classification system would be exacerbated: advanced fuel cycles implement processes such as the separation of used nuclear fuel, which introduce new waste streams of varying characteristics. To be able to manage and dispose of these potential new wastes properly, development of a classification system that would assign appropriate level of management to each type of waste based on its physical properties is imperative. This dissertation explores how characteristics from wastes generated from potential future nuclear fuel cycles could be coupled with a characteristics-based classification framework. A static mass flow model developed under the Department of Energy's Fuel Cycle Research & Development program, called the Fuel-cycle Integration and Tradeoffs (FIT) model, was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices: two modified open fuel cycle cases (recycle in MOX reactor) and two different continuous-recycle fast reactor recycle cases (oxide and metal fuel fast reactors). This analysis focuses on the impact of waste heat load on waste classification practices, although future work could involve coupling waste heat load with metrics of radiotoxicity and longevity. The value of separation of heat-generating fission products and actinides in different fuel cycles and how it could inform long- and short-term disposal management is discussed. It is shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system, and that it is useful to classify waste streams based on how favorable the impact of interim storage is on increasing repository capacity. The need for a more diverse set of waste classes is discussed, and it is shown that the characteristics-based IAEA classification guidelines could accommodate wastes created from advanced fuel cycles more comprehensively than the U.S. classification framework.

Treatment-Based Classification versus Usual Care for Management of Low Back Pain

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-11-1-0657 TITLE: Treatment-Based Classification versus Usual Care for Management of Low Back Pain PRINCIPAL INVESTIGATOR...Treatment-Based Classification versus Usual Care for Management of Low Back Pain 5b. GRANT NUMBER W81XWH-11-1-0657 5c. PROGRAM ELEMENT NUMBER 6...AUTHOR(S) MAJ Daniel Rhon – daniel_rhon@baylor.edu 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

An objective and parsimonious approach for classifying natural flow regimes at a continental scale

NASA Astrophysics Data System (ADS)

Archfield, S. A.; Kennen, J.; Carlisle, D.; Wolock, D.

2013-12-01

Hydroecological stream classification--the process of grouping streams by similar hydrologic responses and, thereby, similar aquatic habitat--has been widely accepted and is often one of the first steps towards developing ecological flow targets. Despite its importance, the last national classification of streamgauges was completed about 20 years ago. A new classification of 1,534 streamgauges in the contiguous United States is presented using a novel and parsimonious approach to understand similarity in ecological streamflow response. This new classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydroecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classes derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges.

[The electronic use of the NANDA-, NOC- and NIC- classifications and implications for nursing practice].

PubMed

Bernhart-Just, Alexandra; Hillewerth, Kathrin; Holzer-Pruss, Christina; Paprotny, Monika; Zimmermann Heinrich, Heidi

2009-12-01

The data model developed on behalf of the Nursing Service Commission of the Canton of Zurich (Pflegedienstkommission des Kantons Zürich) is based on the NANDA nursing diagnoses, the Nursing Outcome Classification, and the Nursing Intervention Classification (NNN Classifications). It also includes integrated functions for cost-centered accounting, service recording, and the Swiss Nursing Minimum Data Set. The data model uses the NNN classifications to map a possible form of the nursing process in the electronic patient health record, where the nurse can choose nursing diagnoses, outcomes, and interventions relevant to the patient situation. The nurses' choice is guided both by the different classifications and their linkages, and the use of specific text components pre-defined for each classification and accessible through the respective linkages. This article describes the developed data model and illustrates its clinical application in a specific patient's situation. Preparatory work required for the implementation of NNN classifications in practical nursing such as content filtering and the creation of linkages between the NNN classifications are described. Against the background of documentation of the nursing process based on the DAPEP(1) data model, possible changes and requirements are deduced. The article provides a contribution to the discussion of a change in documentation of the nursing process by implementing nursing classifications in electronic patient records.

The Blurred Line between Form and Process: A Comparison of Stream Channel Classification Frameworks

PubMed Central

Kasprak, Alan; Hough-Snee, Nate

2016-01-01

Stream classification provides a means to understand the diversity and distribution of channels and floodplains that occur across a landscape while identifying links between geomorphic form and process. Accordingly, stream classification is frequently employed as a watershed planning, management, and restoration tool. At the same time, there has been intense debate and criticism of particular frameworks, on the grounds that these frameworks classify stream reaches based largely on their physical form, rather than direct measurements of their component hydrogeomorphic processes. Despite this debate surrounding stream classifications, and their ongoing use in watershed management, direct comparisons of channel classification frameworks are rare. Here we implement four stream classification frameworks and explore the degree to which each make inferences about hydrogeomorphic process from channel form within the Middle Fork John Day Basin, a watershed of high conservation interest within the Columbia River Basin, U.S.A. We compare the results of the River Styles Framework, Natural Channel Classification, Rosgen Classification System, and a channel form-based statistical classification at 33 field-monitored sites. We found that the four frameworks consistently classified reach types into similar groups based on each reach or segment’s dominant hydrogeomorphic elements. Where classified channel types diverged, differences could be attributed to the (a) spatial scale of input data used, (b) the requisite metrics and their order in completing a framework’s decision tree and/or, (c) whether the framework attempts to classify current or historic channel form. Divergence in framework agreement was also observed at reaches where channel planform was decoupled from valley setting. Overall, the relative agreement between frameworks indicates that criticism of individual classifications for their use of form in grouping stream channels may be overstated. These form-based criticisms may also ignore the geomorphic tenet that channel form reflects formative hydrogeomorphic processes across a given landscape. PMID:26982076

Naïve Bayes classification in R.

PubMed

Zhang, Zhongheng

2016-06-01

Naïve Bayes classification is a kind of simple probabilistic classification methods based on Bayes' theorem with the assumption of independence between features. The model is trained on training dataset to make predictions by predict() function. This article introduces two functions naiveBayes() and train() for the performance of Naïve Bayes classification.

Computer-implemented land use classification with pattern recognition software and ERTS digital data. [Mississippi coastal plains

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1974-01-01

Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

Classification of Dual-Wavelength Airborne Laser Scanning Point Cloud Based on the Radiometric Properties of the Objects

NASA Astrophysics Data System (ADS)

Pilarska, M.

2018-05-01

Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

Fusion and Gaussian mixture based classifiers for SONAR data

NASA Astrophysics Data System (ADS)

Kotari, Vikas; Chang, KC

2011-06-01

Underwater mines are inexpensive and highly effective weapons. They are difficult to detect and classify. Hence detection and classification of underwater mines is essential for the safety of naval vessels. This necessitates a formulation of highly efficient classifiers and detection techniques. Current techniques primarily focus on signals from one source. Data fusion is known to increase the accuracy of detection and classification. In this paper, we formulated a fusion-based classifier and a Gaussian mixture model (GMM) based classifier for classification of underwater mines. The emphasis has been on sound navigation and ranging (SONAR) signals due to their extensive use in current naval operations. The classifiers have been tested on real SONAR data obtained from University of California Irvine (UCI) repository. The performance of both GMM based classifier and fusion based classifier clearly demonstrate their superior classification accuracy over conventional single source cases and validate our approach.

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

Pathohistological classification systems in gastric cancer: Diagnostic relevance and prognostic value

PubMed Central

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-01-01

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer. PMID:24914328

Land use/cover classification in the Brazilian Amazon using satellite images.

PubMed

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira

2012-09-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Land use/cover classification in the Brazilian Amazon using satellite images

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant’Anna, Sidnei João Siqueira

2013-01-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data. PMID:24353353

A comprehensive simulation study on classification of RNA-Seq data.

PubMed

Zararsız, Gökmen; Goksuluk, Dincer; Korkmaz, Selcuk; Eldem, Vahap; Zararsiz, Gozde Erturk; Duru, Izzet Parug; Ozturk, Ahmet

2017-01-01

RNA sequencing (RNA-Seq) is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data) or require a normal distribution assumption. Hence, these methods cannot be directly applied to RNA-Seq data since they violate both data structure and distributional assumptions. However, it is possible to apply these algorithms with appropriate modifications to RNA-Seq data. One way is to develop count-based classifiers, such as Poisson linear discriminant analysis and negative binomial linear discriminant analysis. Another way is to bring the data closer to microarrays and apply microarray-based classifiers. In this study, we compared several classifiers including PLDA with and without power transformation, NBLDA, single SVM, bagging SVM (bagSVM), classification and regression trees (CART), and random forests (RF). We also examined the effect of several parameters such as overdispersion, sample size, number of genes, number of classes, differential-expression rate, and the transformation method on model performances. A comprehensive simulation study is conducted and the results are compared with the results of two miRNA and two mRNA experimental datasets. The results revealed that increasing the sample size, differential-expression rate and decreasing the dispersion parameter and number of groups lead to an increase in classification accuracy. Similar with differential-expression studies, the classification of RNA-Seq data requires careful attention when handling data overdispersion. We conclude that, as a count-based classifier, the power transformed PLDA and, as a microarray-based classifier, vst or rlog transformed RF and SVM classifiers may be a good choice for classification. An R/BIOCONDUCTOR package, MLSeq, is freely available at https://www.bioconductor.org/packages/release/bioc/html/MLSeq.html.

Object-based land cover classification and change analysis in the Baltimore metropolitan area using multitemporal high resolution remote sensing data

Treesearch

Weiqi Zhou; Austin Troy; Morgan Grove

2008-01-01

Accurate and timely information about land cover pattern and change in urban areas is crucial for urban land management decision-making, ecosystem monitoring and urban planning. This paper presents the methods and results of an object-based classification and post-classification change detection of multitemporal high-spatial resolution Emerge aerial imagery in the...

California desert resource inventory using multispectral classification of digitally mosaicked Landsat frames

NASA Technical Reports Server (NTRS)

Bryant, N. A.; Mcleod, R. G.; Zobrist, A. L.; Johnson, H. B.

1979-01-01

Procedures for adjustment of brightness values between frames and the digital mosaicking of Landsat frames to standard map projections are developed for providing a continuous data base for multispectral thematic classification. A combination of local terrain variations in the Californian deserts and a global sampling strategy based on transects provided the framework for accurate classification throughout the entire geographic region.

Supervised DNA Barcodes species classification: analysis, comparisons and results

PubMed Central

2014-01-01

Background Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. Methods In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. Results A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods. Conclusions The classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community. PMID:24721333

Risk-informed radioactive waste classification and reclassification.

PubMed

Croff, Allen G

2006-11-01

Radioactive waste classification systems have been developed to allow wastes having similar hazards to be grouped for purposes of storage, treatment, packaging, transportation, and/or disposal. As recommended in the National Council on Radiation Protection and Measurements' Report No. 139, Risk-Based Classification of Radioactive and Hazardous Chemical Wastes, a preferred classification system would be based primarily on the health risks to the public that arise from waste disposal and secondarily on other attributes such as the near-term practicalities of managing a waste, i.e., the waste classification system would be risk informed. The current U.S. radioactive waste classification system is not risk informed because key definitions--especially that of high-level waste--are based on the source of the waste instead of its inherent characteristics related to risk. A second important reason for concluding the existing U.S. radioactive waste classification system is not risk informed is there are no general principles or provisions for exempting materials from being classified as radioactive waste which would then allow management without regard to its radioactivity. This paper elaborates the current system for classifying and reclassifying radioactive wastes in the United States, analyzes the extent to which the system is risk informed and the ramifications of its not being so, and provides observations on potential future direction of efforts to address shortcomings in the U.S. radioactive waste classification system as of 2004.