Antimicrobial resistance and population structure of methicillin-resistant Staphylococcus aureus recovered from pigs

Three-hundred twenty-eight Belgian farms were sampled for MRSA in 2013. Per farm, 20 pooled nose swabs from 20 animals were analysed by selective enrichment and plating on MRSA selective plate, MRSA-ID (bioMérieux, France) as described before (Nemeghaire et al., 2013). One MRSA strain per farm was further analysed by MRSA identification and typing (spa-typing, sau1-hsdS1 clonal complex (CC) 398 PCR, MLST, SCCmec typing, microarray analysis (Identibac S. aureus Genotyping DNA micro array, Alere Technologies GmbH, Germany), and antimicrobial susceptibility testing was done as described before (Nemeghaire et al., 2013). MRSA was present in 65.6% (95% CI: 60.1%-71%) of the 328 farms sampled. Most isolates (n=205) were positive for the sau1-hsdS1 CC398 PCR. The remaining eight isolates were ST9 (one isolate), ST80 (two isolates), ST239 (one isolate) or ST398 (six isolates). spa types t044, t337 and t4150 were found in the CC80, CC9 and CC8 isolates, respectively. Nineteen spa types were found among the 211 CC398 isolates. Most strains were spa type t011 (n=180). The other types found were t034, t1344, t1451, t1456, t1580, t1985, t2123, t2370, t2922, t3171, t3424, t3854, t4432, t4872, t5452, t5051, t6628, t8100. The isolates belonged to CC8, CC9 and CC80 carried SCCmec cassettes types IVc or V. Most CC398 isolates carried SCCmec V (79%), and less carried SCCmec III (1%) or IVa (18%). A total of 4 isolates carried NT cassettes, one ST239 and 3 CC398. Most strains had additional resistance to 5 antibiotics. Micro array analysis showed a great variety in resistance genes and genes encoding virulence factors including haemolysins, proteases, biofilm production, adhesion factors, immune-evasion factors, the intact hlbgene, putative transport proteins and staphylococcal superantigen-like proteins from the vSaα genomic island. Capsule 5-related genes, the egc-like cluster, were less prevalent. Non CC398 strains carried additional virulence characteristics like leukocidins (lukED, lukPV), an exfoliatin (etd), and an epidermal cell differentiation inhibitor (edinB). The sau1-hsdS1 clonal complex (CC) 398 PCR did not detect all CC398 strains in our hands, however it remains a good screening method. The prevalence of MRSA in Belgium seems to be stable over time, comparing results going back to 2006. The diversity of CC398 seems to have increased, with the appearance of multiple spa types within CC398 and MLST types other than CC398. ST 239, a sequence type belonging to the healthcare-associated CC8 clonal complex, was found in pigs as it was found before in bovines and poultry in Belgium. The presence of other MRSA (and possibly also MSSA) offers the possibility to the LA-MRSA CC398 acquiring more virulence and resistance genes. This is a potential risk for human and animal health given the possibility of this strain to spread to different animal species

Antimicrobial resistance and population structure of Staphylococcus aureus recovered from pigs in Belgium

Staphylococcus aureus is a common facultative pathogen that has since long been recognized as a burden in both human and veterinary medicine. S. aureus is well known to be frequently resistant to antimicrobial agents which may lead to complications in the treatment of its infections and increase the cost of treatments. During the last decade, an increasing number of studies reported the presence of methicillin-resistant Staphylococcus aureus (MRSA) in animals. Most studies have focused on the asymptomatic carriage of MRSA among pigs, in which clonal complex (CC) 398 is the dominant lineage. During 2013, a survey was performed in different pig farms randomly selected over Belgium, with the aim of monitoring the current epidemiology and antimicrobial susceptibility of MRSA among asymptomatic pigs. From 328 farms nose swabs were taken from 20 animals and pooled. MRSA was isolated using the standard method proposed by the European Food Safety Authority (EFSA). MRSA identification was performed using the triplex 16S rRNA-mecA-nuc PCR. All isolates were characterised by means of susceptibility testing by a microbroth-dilution method using epidemiological cut-off values (Eucast), SCCmec typing, spa-typing and by the sau1-hsdS1 clonal complex (CC) 398 PCR. CC398 PCR negative isolates were subjected to multi-locus sequence typing (MLST). Selected isolates were subjected to DNA microarray-based typing for detection of resistance and virulence genes. MRSA was detected in 215 farms [65.6% (95% CI: 60.1%-71%)] out of 328 farms sampled. Most isolates (n=207) were positive for the sau1-hsdS1 CC398 PCR. The remaining eight isolates were ST9 (one isolate), ST80 (two isolates), ST239 (one isolate) or ST398 (four isolates) as demonstrated by MLST. A total of 22 different spa types were identified. The spa types t044, t337 and t4150 were found in the ST80, ST9 and ST239 isolates, respectively. Nineteen spa types were found among the CC398 isolates, but most were t011 (n=180, 85%). Regarding to the SCCmec typing, most isolates carried SCCmec V, and less carried SCCmec IV or III. More than 90% of the isolates were epidemiological resistant to tetracycline and trimethoprim and high resistance rates (between 66% and 45%) were also found for ciprofloxacin, clindamycin, erythromycin, kanamycin and gentamicin. Lower epidemiological resistance levels (between 30% and 10%) were detected for streptomycin, fusidic acid, sulfamethoxazole, quinupristin/dalfopristin, tiamulin, rifampicin, chloramphenicol and mupirocin. All isolates were susceptible for vancomycin. More than 90% of the isolates were multi-resistant, and half of them were resistant to at least seven different antibiotics. Microarray analysis showed that most genes were homogeneously distributed among the CC398 isolates. The non-CC398 isolates carried additional virulence genes, as the egc-like cluster with enterotoxins genes (seg, seh, sei, selm, seln, selo, selu). Interestingly, the ST80 strains carried the leukocidin Panton-Valentine (lukPV) and lukED genes. Regarding to antimicrobial resistance genes, all CC398 isolates investigated carried the tetracycline resistance gene tet(M). Most CC398 isolates carried the bla operon (blaZ, blaI, and blaR) encoding for penicillin-ampicillin resistance and the tetracycline resistance gene tet(K). Some CC398 isolates carried genes encoding resistance to the macrolide-lincosamide-streptogramin group [erm(B), erm(C), lnu(A), vga(A)], aminoglycosides (aacA-aphD, aadD, aphA3, sat) and/or chloramphenicol (fexA). One fexA positive isolate was additionally positive for the multi-resistance gene cfr. The MRSA prevalence among pigs in Belgium remains similar to previous studies performed on 2007 and 2009. As has been demonstrated before, the CC398 isolates were highly multi-resistant. However, in this survey there is a larger diversity in spa-types than ever detected before. Moreover, in this survey we have detected the European clone ST80-IV, which corresponded to the main community-acquired (CA-) MRSA clone in Europe. The ST80-IV had the Panton-Valentine leucocidin and had emerged recently as a cause of healthcare-associated infections. The recovery of this CA-MRSA from livestock indicates that one should remain vigilant to the evolution of LA-MRSA CC398

Osteolysis: a literature review of basic science and potential computer-based Image processing detection methods

Osteolysis is one of the most prominent reasons of revision surgeries in total joint arthroplasty. is biological phenomenon is induced by wear particles and corrosion products that stimulate inflammatory biological response of surrounding tissues. e eventual responses of osteolysis are the activation of macrophages leading to bone resorption and prosthesis failure. Various factors are involved in the initiation of osteolysis from biological issues, design, material specifications, and model of the prosthesis to the health condition of the patient. Nevertheless, the factors leading to osteolysis are sometimes preventable. Changes in implant design and polyethylene manufacturing are striving to improve overall wear. Osteolysisis clinically asymptomatic and can be diagnosed and analyzed during follow-up sessions through various imaging modalities and methods, such as serial radiographic, CT scan, MRI, and image processing-based methods, especially with the use of artificial neural network algorithms. Deep learning algorithms with a variety of neural network structures such as CNN, U-Net, and Seg-UNet have proved to be efficient algorithms for medical image processing specifically in the field of orthopedics for the detection and segmentation of tumors. ese deep learning algorithms can effectively detect and analyze osteolytic lesions well in advance during follow-up sessions in order to administer proper treatments before reaching a critical point. Osteolysis can be treated surgically or nonsurgically with medications. However, revision surgeries are the only solution for the progressive osteolysis. In this literature review, the underlying causes, mechanisms, and treatments of osteolysis are discussed with the main focus on the possible computer-based methods and algorithms that can be effectively employed for the detection of osteolysis