1,721,019 research outputs found

    Methicillin-resistant staphylococci in clinical bovine mastitis: occurrence, molecular analysis, and biofilm production

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    Staphylococcus aureus is an important pathogen that causes mastitis in cattle, and the emergence of methicillin-resistant S. aureus (MRSA) poses a threat to veterinary and human medicine. The aims of the study were to investigate the prevalence of MRSA and methicillin-resistant coagulase-negative staphylococci (MR-CoNS) isolated from clinical mastitis, their ability to form biofilms, and the antimicrobial susceptibility of S. aureus strains. In addition, the Staphylococcal Cassette Chromosome mec (SCCmec) type, spa type and the presence of Panton-Valentine Leucocidin in MRSA were evaluated. A total of 326 staphylococcal strains were screened by multiplex-PCR for S. aureus and Staphylococcus intermedius group (SIG) identification. The S. aureus strains (n = 163) were subjected to phenotypic testing for antimicrobial susceptibility and biofilm formation. Molecular analysis was performed on MRSA mecA-positive strains. Of 163 S. aureus isolates, 142 strains (87.1%) were resistant to at least one antibiotic, and all 19 MRSA strains were resistant to at least four out of five antibiotics tested. All S. aureus strains harboured the icaA gene and were biofilm producers. Nineteen MR-CoNS strains were also isolated. The most prevalent spa types among MRSA were t001 (57.9%) and t037 (31.6%), while one MRSA was type t008 and one was type t041. Most MRSA were SCCmec type I (63.2%) and III (31.6%) and only one strain was type IV. None of the MRSA isolates had the PVL gene. The prevalence of multidrug-resistant S. aureus in bovine mastitis is a serious concern. The finding of MRSA with spa types predominant in humans and infrequent in Italian cows and with SCCmec infrequently found in bovine milk or cheese suggest a human origin of these strains. The ability of MRSA and MR-CoNS involved in bovine mastitis to be transferred to humans and vice versa poses a public health concern

    Estimating the spread of paratuberculosis within dairy cattle using a deterministic mathematical model

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    A mathematical deterministic model is used to describe the spread of paratuberculosis within dairy cattle during a 9 weeks period. The number of susceptible and exposed calves, and that of susceptible and infective cows are calculated over time. Either a small ((A) 190 animals) or a large ((B) 570 animals) dairy cattle is taken into consideration, assuming the initial presence of one infective cow. After 9 weeks, one can infer that: (A) there will be about 183 animals left in cattle (A), of which 25 cows and 26 calves will be infected, and 76 cows and 56 calves still susceptible, (B) there will be about 551 animals in cattle (B), of which 301 cows and 245 calves will be infected and only 2 cows and 3 calves still susceptibl

    Enrofloxacin resistance in Escherichia coli isolated from poultry: preliminary analysis of gyrA and parC sequences

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    Escherichia coli are usually common inhabitants of the gastrointestinal tract of birds, although avian pathogenic strains can cause several diseases. Furthermore, gut of birds can be a reservoir of zoonotic E. coli, and contamination of poultry products may occur during slaughtering and processing procedures. Enrofloxacin (ENR) is commonly used in poultry farming, although recently a prudent and rationale use of fluoroquinolone (FQ) in farm animals is recommended by the European Union. The most frequent mechanism of FQ resistance in E. coli is represented by alterations occurring in genes encoding for DNA gyrase and topoisomerase IV. The aims of this study were to evaluate the ENR resistance in E. coli isolated from poultry and to investigate mutations in the sequences of gyrA and parC genes. Swab samples collected from poultry were tested by bacteriology. Pure cultures of E. coli were used for MIC and for DNA extraction. DNA was amplified by PCR to obtain a 347 bp fragment of gyrA gene and a 964 bp fragment of parC gene. PCR products were sequenced and analysed. A total of 12 E. coli isolates resulted resistant to ENR by MIC. Further 12 ENR-susceptible E. coli were randomly selected among all susceptible isolates. Predicted amino acid sequences of gyrA and parC were aligned and analyzed blindly. Most of resistant E. coli isolates showed mutations at codons 83 and 87 of gyrA and at codon 80 of parC. In particular, 11 resistant isolates had Ser83Leu mutation, that was present also in 3 susceptible isolates. No other mutations at codons 83 and 87 of gyrA and at codon 80 of parC were found in susceptible isolates. Among resistant isolates, 10 possessed mutations at gyrA codon 87 and 11 isolates showed mutations at parC codon 80. Mutations were Asp87Asn (n=8), Asp87Gly (n=1), Asp87Tyr (n=1) in gyrA and Ser80Ile (n=9) and Ser80Arg (n=2) in parC. Evaluation of mutations at codon 80 of parC resulted the most sensitive (91.7%) and specific (100%) test for distinguishing ENR-susceptible to ENR-resistant isolates. Finally, 7 out of 12 ENR-resistant isolates showed two gyrA mutations (Ser83Leu and Asp87Asn) coupled with a substitution in parC (Ser80Ile); the same findings have been reported in E. coli isolated from poultry and resulted resistant to many FQs (ciprofloxacin, danofloxacin, difloxacin, enrofloxacin, flumequine, marbofloxacin, nalidixic acid, and sarafloxacin). These isolates showed also the highest values of MIC

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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