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Methicillin-Resistant

Methicillin-Resistant: A type of Staphylococcus aureus bacterium that has developed resistance to the antibiotic methicillin and other related antibiotics.
This makes infections with Methicillin-Resistant Staphylococcus aureus (MRSA) more difficult to treat.
MRSA can cause a range of illnesses, from skin and wound infections to more severe and life-threatening conditions.
Identifying effective protocols and strategies is crucial for researching and managing this significant public health concern.

Most cited protocols related to «Methicillin-Resistant»

National Healthcare Safety Network (NHSN) Pathogens Report

The CLABSIs,⁷ CAUTIs,⁸ select VAEs,⁹ and SSIs¹⁰ that occurred between 2015–2017 and had been reported to the NHSN’s Patient Safety Component as of July 1, 2018, were included in this report. These HAIs were reported by acute-care hospitals, critical access hospitals, LTACHs, and IRFs from all US states and territories. Unless otherwise noted, CLABSI data included events classified as mucosal barrier injury laboratory-confirmed bloodstream infection (MBI-LCBI). VAE data were limited to events classified as possible ventilator-associated pneumonia (PVAP) because this is the only subtype of VAE for which a pathogen can be reported. Asymptomatic bacteremic urinary tract infections, CLABSIs reported from IRFs, and outpatient SSIs were excluded.
The NHSN protocols provide guidance for attributing device-associated (DA) HAIs (ie, CLABSIs, CAUTIs, and PVAPs) to a CDC-defined location type, and SSIs to a CDC operative procedure code. Due to known differences in pathogens and resistance patterns between adult and pediatric populations,^{11 ,12 (link)} this report was limited to DA HAIs attributed to adult location types, and to SSIs that occurred in patients ≥18 years old at the time of surgery. Comparable data from pediatric locations and patients are described in a companion report.^{13 (link)}Unless otherwise noted, DA HAIs were stratified into 5 mutually exclusive location categories: hospital wards (inclusive of step-down, mixed acuity, and specialty care areas), hospital intensive care units (ICUs), hospital oncology units (ie, oncology ICUs and wards), LTACHs (ie, LTACH ICUs and wards), and IRFs (ie, freestanding IRFs and CMS-certified IRF units located within a hospital). SSI data were stratified into mutually exclusive surgical categories based on the operative procedure code. Pathogen distributions were also analyzed separately for each operative procedure code and are available in the online supplement.¹⁴Up to 3 pathogens and their antimicrobial susceptibility testing (AST) results can be reported to the NHSN for each HAI. The AST results for the drugs included in this analysis were reported using the interpretive categories of “susceptible” (S), “intermediate” (I), “resistant” (R), or “not tested.” Instead of “intermediate,” cefepime had the category interpretation of “intermediate/susceptible-dose dependent” (I/S-DD), which was treated as I for this analysis. Laboratories are expected to follow current guidelines from the Clinical and Laboratory Standards Institute (CLSI) for AST.¹⁵ Naming conventions for pathogens generally adhered to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) Preferred Term.¹⁶ In some cases, pathogens were grouped by genus or clinically recognized group (eg, viridans group streptococci) (Appendices A2–A4 online). Results for Klebsiella spp were limited to K. pneumoniae and K. oxytoca; K. aerogenes was considered part of Enterobacter spp due to the timing of the NHSN’s adoption of its name change.^{17 (link)}Staphylococcus aureus was defined as methicillin-resistant (MRSA) if the isolate was reported as R to oxacillin, cefoxitin, or methicillin. Enterococcus spp isolates were defined as vancomycin-resistant (VRE) if they tested R to vancomycin. VRE data were analyzed for all HAIs except PVAP because Enterococcus spp are excluded from the NHSN’s PVAP surveillance definition under most scenarios. Carbapenem-resistant Enterobacteriaceae (CRE) were defined as Klebsiella spp, Escherichia coli, or Enterobacter spp that tested R to imipenem, meropenem, doripenem, or ertapenem. All other pathogen-antimicrobial combinations (phenotypes) were described using a metric for nonsusceptibility, which included pathogens that tested I or R to the applicable drugs. To be defined as nonsusceptible to extended-spectrum cephalosporins (ESCs), pathogens must have tested I or R to either ceftazidime or cefepime (Pseudomonas aeruginosa) or to ceftazidime, cefepime, ceftriaxone, or cefotaxime (Klebsiella spp and E. coli). For Enterobacter spp, evaluation of nonsusceptibility to ESCs was limited to cefepime due to Enterobacter’s inducible resistance to other ESCs. Fluoroquinolone nonsusceptibility was defined as a result of I or R to either ciprofloxacin or levofloxacin (P. aeruginosa) or to ciprofloxacin, levofloxacin, or moxifloxacin (E. coli). Carbapenem nonsusceptibility in P. aeruginosa and Acinetobacter spp was defined as a result of I or R to imipenem, meropenem, or doripenem. Nonsusceptibility to aminoglycosides was defined as a result of I or R to gentamicin, amikacin, or tobramycin. Finally, multi-drug-resistance (MDR) was approximated by adapting previously established definitions^{18 (link)} that require nonsusceptibility to at least 1 agent within 3 different drug classes. For Enterobacteriaceae and P. aeruginosa, 5 classes were considered in the criteria: ESCs (or cefepime for Enterobacter spp), fluoroquinolones, aminoglycosides, carbapenems, and piperacillin (PIP) or piperacillin/tazobactam (PIPTAZ). A sixth class, ampicillin/sulbactam, was included in the criteria for Acinetobacter spp.
Data were analyzed using SAS version 9.4 software (SAS Institute, Cary, NC). For all HAIs and pathogens, absolute frequencies and distributions were calculated by HAI, location, and surgical category. The 15 most commonly reported pathogens were identified, and their frequencies and ranks within each stratum were calculated. A pooled mean percentage nonsusceptible (%NS) was calculated for each phenotype as the sum of nonsusceptible (or resistant) pathogens, divided by the sum of pathogens tested for susceptibility, and multiplied by 100. Percentage NS was not calculated for any phenotype for which <20 pathogens were tested. Differences in the %NS across location types or surgical categories were assessed for statistical significance using a mid-P exact test, and P < .05 was considered statistically significant. The percentage of pathogens with reported susceptibility results (referred to as “percentage tested”) is defined elsewhere^{3 (link)} and was calculated for each bacterial phenotype, as well as for select Candida spp. Pathogens and susceptibility data for CLABSIs categorized as MBI-LCBI were analyzed separately and are presented in the online supplement.¹⁴“Selective reporting” occurs when laboratories suppress AST results as part of antimicrobial stewardship efforts. This practice could contribute to a higher number of pathogens reported to the NHSN as “not tested” to certain drugs. To assess the impact of selective reporting on the national %NS, we applied an alternate calculation for CRE and ESC nonsusceptibility. If a pathogen was reported as “not tested” to carbapenems, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, ampicillin/sulbactam, amoxicillin/clavulanic acid, PIPTAZ, cefazolin, cefoxitin, or cefotetan. If a pathogen was reported as “not tested” to ESCs, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, aztreonam, or cefazolin. Therefore, the number of tested isolates increases under the alternate calculation. Percentage NS was calculated using both the traditional (ie, strictly as reported) and alternate approaches.
Statistical analyses were not performed to test for temporal changes in the %NS; thus, this report does not convey any conclusions regarding changes in resistance over time. Due to differences in the stratification levels, inclusion criteria, and patient populations, the %NS values in this report should not be compared to those published in previous iterations of this report.

Weiner-Lastinger L.M., Abner S., Edwards J.R., Kallen A.J., Karlsson M., Magill S.S., Pollock D., See I., Soe M.M., Walters M.S, & Dudeck M.A. (2019). Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017. Infection control and hospital epidemiology, 41(1), 1-18.

Publication 2019

Acinetobacter Adult Amikacin Aminoglycosides Amox clav Ampicillin ampicillin-sulbactam Antimicrobial Stewardship Asymptomatic Infections Aztreonam Bacteremia Bacteria Blood Circulation Candida Carbapenem-Resistant Enterobacteriaceae Carbapenems Cefazolin Cefepime Cefotaxime Cefotetan Cefoxitin Ceftazidime Ceftriaxone Cephalosporins Ciprofloxacin Clinical Laboratory Services Conferences Dietary Supplements Doripenem Enterobacter Enterobacteriaceae Enterococcus Ertapenem Escherichia coli Fluoroquinolones Gentamicin Imipenem Injuries Klebsiella Klebsiella oxytoca Klebsiella pneumoniae Laboratory Infection Lanugo Levofloxacin Medical Devices Meropenem Methicillin Methicillin-Resistant Microbicides Moxifloxacin Mucous Membrane Multi-Drug Resistance Neoplasms Operative Surgical Procedures Outpatients Oxacillin pathogenesis Patients Patient Safety Pets Pharmaceutical Preparations Phenotype Piperacillin Piperacillin-Tazobactam Combination Product Pneumonia, Ventilator-Associated polyvinylacetate phthalate polymer Population Group Pseudomonas aeruginosa Sepsis Staphylococcus aureus Infection Streptococcus viridans Substance Abuse Detection Susceptibility, Disease Tobramycin Urinary Tract Vancomycin Vancomycin Resistance Wound Infection

Validation of MLVA for MRSA Surveillance

In this study we included a collection of 2525 strains consisting of i) a test set of 86 S. aureus+10 S. epidermidis isolates, ii) a set of 1681 human and 100 pig-related S. aureus isolates used for extensive validation, iii) 658 S. aureus isolates used to assess the potential of MLVA to identify outbreaks. The test set included reference strains and was used for the initial set up of the MLVA. The isolates used for extensive validation were collected for the national S. aureus surveillance by the department of bacterial typing of the Laboratory of Infectious Diseases and Perinatal Screening of the National Institute for Public Health and the Environment. Of this strain set, 1781 were collected from 2005 to 2007 out of which 1681 strains were isolated from humans and 100 from pigs. For this study we used 393 isolates collected in 2005, 617 collected in 2006 and 671 isolates collected in 2007. The isolates were collected during the first 3 months in each of the 3 years and represented approximately 20% of the total number of isolates collected for the national surveillance during that time period. Of the 1681 strains from humans, 135 were isolated from blood, 831 originated from nasal, throat or perineum swabs and the remainder was predominantly isolated from wound infections. Approximately 87% of the strains isolated from humans and all strains isolated from pigs were methicillin-resistant S. aureus (MRSA). The collection of 1681 strains isolated from humans also included 163 strains that were part of the Dutch strains collected for the EARSS project (http://www.rivm.nl/earss/) 156 of which were methicillin sensitive S. aureus (MSSA). The 100 MRSA strains isolated from pigs were all collected in 2007. In addition, a set of 658 MRSA isolates collected for the national S. aureus surveillance in 2008 was used for a preliminary assessment of the epidemiological potential of the MLVA.

Schouls L.M., Spalburg E.C., van Luit M., Huijsdens X.W., Pluister G.N., van Santen-Verheuvel M.G., van der Heide H.G., Grundmann H., Heck M.E, & de Neeling A.J. (2009). Multiple-Locus Variable Number Tandem Repeat Analysis of Staphylococcus Aureus: Comparison with Pulsed-Field Gel Electrophoresis and spa-Typing. PLoS ONE, 4(4), e5082.

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Publication 2009

Bacterial Infections Blood Disease Outbreaks Homo sapiens Methicillin Methicillin-Resistant Nose Perineum Pharynx Strains Sus scrofa Wound Infection

Assessing Blood Culture Utilization for Major AMR Pathogens

We used the definitions of infection origin as proposed by WHO GLASS.¹ In brief, community-origin (or hospital-origin) BSI was defined for patients in the hospital within (or longer than) the first two calendar days of admission when the first blood specimens culture positive for a pathogen were taken.¹ A blood culture episode was defined as all blood culture specimens taken within two calendar days beginning when a blood culture specimen was taken.
We focused on rates of blood culture utilization in relation to BSI caused by Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Acinetobacter spp. and Pseudomonas aeruginosa because these are the top five pathogens attributable to deaths caused by AMR infections in Thailand⁸ (link) and the EU and the European Economic Area.⁹ (link)
Proportions of 3rd generation cephalosporin resistant E. coli (3GCREC) and K. pneumoniae (3GCRKP), methicillin-resistant S. aureus (MRSA), and carbapenem-resistant Acinetobacter spp. (CRACI) and P. aeruginosa (CRPA) were defined as the ratio of the number of patients having a blood culture positive for 3GCREC, 3GCRKP, MRSA, CRACI and CRPA, and the total number of patients with at least one positive blood culture with the given organism, respectively. Only the first isolate per patient, per pathogen, per study period was included in the analyses. Supplementary text describes how all parameters were estimated.¹ ^,¹⁰
We developed a new variable ‘proportion of patients having a blood culture taken within ±1 calendar day of the day when a parenteral antibiotic was started and continued for at least four consecutive days.’ We included patients who died, were discharged to a hospice or transferred to another hospital before completing four consecutive days of antibiotics and had antibiotics continuously until the day prior to death, a hospice discharge or transfer, respectively.¹¹ (link) We included consecutive calendar days with any parenteral antibiotics after a parenteral antibiotic was started. We used four consecutive days of parenteral antibiotics as a proxy for presumed severe infection,¹¹ (link) in which blood culture is generally recommended.¹² (link)^,¹³ (link)

Lim C., Hantrakun V., Teerawattanasook N., Srisamang P., Teparrukkul P., Sumpradit N., Turner P., Day N.P., Cooper B.S., Peacock S.J, & Limmathurotsakul D. (2021). Impact of low blood culture usage on rates of antimicrobial resistance. The Journal of Infection, 82(3), 355-362.

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Publication 2021

Acinetobacter Antibiotics Blood Culture Carbapenems Cephalosporins Escherichia coli Europeans Hospice Care Infection Klebsiella pneumoniae Methicillin-Resistant Parenteral Nutrition pathogenesis Patient Discharge Patients Pseudomonas aeruginosa Staphylococcus aureus Infection

Sequencing and Assembling S. aureus Genomes

Ethical approval for sequencing S. aureus isolates from routine clinical samples and linkage to patient data without individual patient consent in Oxford and Brighton in the United Kingdom was obtained from Berkshire Ethics Committee (10/H0505/83) and the United Kingdom National Information Governance Board [8-05(e)/2010]. For all isolates, DNA was extracted and sequenced using the Illumina HiSeq 2000 platform (San Diego, CA, USA) as previously described (5 (link)). To assess sequencing quality, reads were mapped to reference strain MRSA 252 (GenBank accession no. BX571856.1) using Stampy v1.0.18 (6 (link)). MRSA 252 was chosen as it contains staphylococcal cassette chromosome mec (SCCmec), has been capillary sequenced (7 (link)), and belongs to a common United Kingdom methicillin-resistant S. aureus (MRSA) clone (EMRSA 16). To obtain whole genomes for BLAST, reads were then de novo assembled using Velvet v1.0.18 (8 (link)). Samples were excluded if they failed quality checks either on mapping (<70% coverage of reference genome after filtering) or assembly (<50% of the genome in contigs > 1 kb).

Gordon N.C., Price J.R., Cole K., Everitt R., Morgan M., Finney J., Kearns A.M., Pichon B., Young B., Wilson D.J., Llewelyn M.J., Paul J., Peto T.E., Crook D.W., Walker A.S, & Golubchik T. (2014). Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing. Journal of Clinical Microbiology, 52(4), 1182-1191.

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Publication 2014

Capillaries Chromosomes Clone Cells Ethics Committees Genome Methicillin-Resistant Patients Staphylococcus

Hairpin-Mediated Assembly of DNA Fragments

Genomic DNA for two strains of S. aureus was purchased from the American Type Culture Collection (ATCC): the methicillin-sensitive strain FDA 209 and the methicillin-resistant strain Mu50. A known variant in S. aureus strains was PCR amplified from these strains using Phusion DNA polymerase from New England Biolabs (NEB) with manufacturer recommended cycling conditions and the primers 5′-GTACGGGTCTCACCCGGTTAACTGCACCTGCATTAA-3′ and 5′-CCTAAGGTCTCGGAAGGAAATTATTTCGAAAAAAGA-3′. For demonstration of this approach on longer fragments, a 1 kb fragment of the ΦX174 genome (NEB) was PCR amplified with Phusion DNA polymerase using manufacturer recommended cycling parameters and the primers 5′-GTACGGGTCTCACCCGAGGCTCTAATGTTCCTAACC-3′ and 5′-CCTAAGGTCTCGGAAGATCTGCTTATGGAAGCCAAG-3′. In all cases, the primers contain a restriction site for the enzyme BsaI. The PCR products were purified using PCR purification columns (Qiagen) and digested with the restriction enzyme BsaI (NEB). The digested PCR products were then ligated to two hairpin-forming oligonucleotides. For the S. aureus products, the hairpin oligonucleotides were 5′-CTTCTCTCTCTCTTTTCCTCCTCCTCCGAAGAAGAAGCCGAGAGAGA-3′ and 5′-CGGGTTTGTTGCAAAGCCTAAACCAATATTGATACATTAGCAACAAA-3′. For the the ΦX174 PCR products, the hairpin oligonucleotides consisted of the sequences 5′-CGGGTCTCTCTCTTTTCCTCCTCCTCCGTTGTTGTTGTTGAGAGAGA-3′ and 5′-CTTCTCTCTCTCTTTTCCTCCTCCTCCGTTGTTGTTGTTGAGAGAGA-3′. The hairpin-forming oligonucleotides contained overhangs complementary to the BsaI product overhangs. Prior to ligation, the hairpins were annealed in stem–loop structures by diluting to 20 μM in the presence of 10 mM Tris (pH 7.5) and 100 mM NaCl. Annealed hairpins were added at molar excess relative to the insert and ligated using T4 DNA Ligase (NEB). Failed ligation products were removed through digestion in the presence of ExoIII and ExoVII exonucleases (NEB and USB, respectively).

Travers K.J., Chin C.S., Rank D.R., Eid J.S, & Turner S.W. (2010). A flexible and efficient template format for circular consensus sequencing and SNP detection. Nucleic Acids Research, 38(15), e159.

Publication 2010

Digestion DNA-Directed DNA Polymerase DNA Restriction Enzymes Exonuclease Genome Ligation Methicillin Methicillin-Resistant Molar Oligonucleotide Primers Oligonucleotides Sodium Chloride Staphylococcus aureus Stem, Plant Strains T4 DNA Ligase Tromethamine

Most recents protocols related to «Methicillin-Resistant»

Bacterial Uptake of Radiotracer F-PABA

Not available on PMC !

Example 3

The ability of different bacterial species to take up [¹⁸F]F-PABA was studied. The radiotracer accumulated in both methicillin sensitive S. aureus (MSSA, Newman) and methicillin-resistant S. aureus (MRSA), as well as the Gram negative bacteria E. coli and Klebsiela pneumoniae.

In the case of MSSA we also demonstrated that heat-killed cells were unable to take up [¹⁸F]F-PABA (FIG. 1). In contrast, [¹⁸F]F-PABA was not taken up by Enterococcus faecalis. E. faecalis has a folate salvage pathway and can take up folate from the environment. Thus, folic acid biosynthesis is dispensable in this organism, which also explains why sulfonamides are not used to treat infection by E. faecalis. These studies suggest that F-PABA uptake depends on on the de novo biosynthesis of folate.

US11857352B2. Positron imaging tomography imaging agent composition and method for bacterial infection (2024-01-02). The Research Foundation for the State University of New York [US]. Inventors: Peter Tonge [US], Zhuo Zhang [US], Peter Smith-Jones [US], Li Liu [US], Hui Wang [US].

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Patent 2024

4-Aminobenzoic Acid Anabolism Bacteria Cells Enterococcus faecalis Escherichia coli Folate Folic Acid Gram Negative Bacteria Infection Klebsiella pneumoniae Methicillin Methicillin-Resistant Pneumonia Staphylococcus aureus Sulfonamides

MRSA Detection in Co-Infection Model

Not available on PMC !

Example 4

Detection of MRSA was tested in a model of co-infection with excess methicillin-resistant Staphylococcus epidermidis (MRSE). In the specific model tested, MRSA (GP1822) was present at 10′ CFU/mL, either alone (MRSA Control); with MRSE at 10⁶CFU/mL (MRSA_MRSE 1e6); or with MRSE at 107 CFU/mL (MRSA_MRSE 1e7) (FIG. 4). Results showed no loss in detection under any condition, with positivity seen in 12/12 samples tested. Thus, the assay was able to detect MRSA in the presence of 1,000-fold and 10,000-fold excesses of MRSE.

US11859257B2. Compositions and methods for detecting Staphylococcus aureus (2024-01-02). Gen-Probe Incorporated [US]. Inventors: Patrick Peterson [US], Paul Darby [US], Matthias Jost [US], Siobhan Miick [US], Matthew Brentnall [US], JoAnn Jackson [US].

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Patent 2024

Biological Assay Coinfection Methicillin-Resistant Methicillin-Resistant Staphylococcus aureus Staphylococcus epidermidis Vision

Differentiation of MRSA using Photoacoustics

In order to interpret the photoacoustic data provided by the flow cytometer, we used k-means clustering to guide our differentiation between methicillin resistant and susceptible samples (28 ). Although a simple interpretation of the number of bacteria after oxacillin treatment compared to the number in the untreated subsample should obviously indicate whether the bacteria was methicillin resistant or not, we used a formal method to automatically determine resistance. K-means, like other clustering methods, takes data points in a space of one or more dimensions and determines natural groupings of those points by proximity. Given a number of clusters, k, the algorithm separates all points into that number of groups. Since we are only interested in resistant and susceptible groups, we chose k = 2. We took the ratio of treated detection numbers over untreated numbers resulting in 13 numbers, approximately in the range of 0 to 1. Lower numbers would indicate that oxacillin was effective in decreasing the S. aureus population. However, there was no ad hoc threshold for determining antibiotic resistance. We applied k-means with two clusters to this data set. We used the Matlab function, kmeans, which uses Lloyd's algorithm. For simplicity, we used Euclidean distance for measuring and establishing iterative clusters. This analysis resulted in two clearly defined clusters for MRSA and methicillin susceptible samples.

Edgar R.H., Samson A.P., Kowalski R.P., Kellum J.A., Hempel J., Viator J.A, & Jhanji V. (2023). Differentiating methicillin resistant and susceptible Staphylococcus aureus from ocular infections using photoacoustic labeling. Frontiers in Medicine, 10, 1017192.

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Publication 2023

Antibiotic Resistance, Microbial Bacteria Methicillin Methicillin-Resistant Methicillin-Resistant Staphylococcus aureus Oxacillin Staphylococcus aureus

Ceftaroline Susceptibility in MRSA

This prospective study was conducted in the Department of Microbiology over a period of 9 months from April 2021 to December 2021 after obtaining clearance from the Ethical Committee. Fifty non-duplicate isolates of Methicillin Resistant S. aureus strains isolated from various clinical samples were included in the study. Isolates which showed gram positive cocci in clusters on grams stain and gave positive results on catalase, slide and tube coagulase where identified as S. aureus.
Screening for methicillin resistance was done by modified Kirby Bauer disc diffusion method using cefoxitin (30 µg) discs. A zone size of ≥22 mm was interpreted as methicillin sensitive and ≤21 mm was interpreted as methicillin resistant as per Clinical and Laboratory Standards Institute (CLSI) guidelines (23 ). S. aureus American Type Culture Collection (ATCC) strain 25923 and S. aureus ATCC strain 43300 were used as susceptibility and resistance controls respectively. Isolates which were Methicillin sensitive were excluded from the study. Antimicrobial susceptibility of the isolates was done by Kirby Bauers disc diffusion
Testing for ceftaroline susceptibility was done by E- test strip method. The ceftaroline E-test strips (0.002–32 µg/mL) was obtained from Biomerieux, France. The E- test strips were placed on the lawn culture of the organism and the plates were incubated at 37°C for 18–24 hours. MIC's were read where the ellipse intersects the MIC (Minimum Inhibitory Concentration) scale. Since E-test strip has continuous gradient, MIC values “in-between” two-fold dilutions can be obtained. These values were rounded up to next two-fold dilution before categorisation. MICs were interpreted according to EUCAST version 11.0 and CLSI 2021.
EUCAST version 11.0 for Ceftaroline (In pneumonia) - ≤1- Susceptible, > 1- Resistant
EUCAST version 11.0 for Ceftaroline (For conditions other than pneumonia)-≤1- Susceptible, >2- Resistant
CLSI 2021- ≤1- Susceptible, 2–4(Susceptible Dose Dependent), ≥8- Resistant.

, & Sachu A. (2023). Ceftaroline Susceptibility among Isolates of MRSA: A Comparison of EUCAST and CLSI Breakpoints. Ethiopian Journal of Health Sciences, 33(1), 143-150.

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Publication 2023

Catalase Cefoxitin ceftaroline Clinical Laboratory Services Coagulase Gram-Positive Cocci Kirby-Bauer Disk-Diffusion Method Lung Diseases Methicillin Methicillin-Resistant Methicillin Resistance Microbicides Minimum Inhibitory Concentration Pneumonia Stains Staphylococcus aureus Strains Susceptibility, Disease Technique, Dilution

Evaluating Antibacterial Efficacy of Drug Elution

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Publication 2023

Agar Anti-Bacterial Agents Antibiotics, Antitubercular Biological Assay Clinical Laboratory Services Diffusion Hypersensitivity Methicillin-Resistant Methicillin-Resistant Staphylococcus aureus Microbicides Pharmaceutical Preparations Psychological Inhibition Staphylococcus aureus Susceptibility, Disease Vancomycin

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What are the different types or variations of Methicillin-Resistant?

Methicillin-Resistant is a type of Staphylococcus aureus (MRSA) bacterium that has developed resistance to the antibiotic methicillin and other related antibiotics. There are two main types of MRSA: 1. Community-associated MRSA (CA-MRSA): This type is typically transmitted in community settings, such as schools, gyms, or other public places, and often causes skin and soft tissue infections. 2. Healthcare-associated MRSA (HA-MRSA): This type is commonly found in healthcare settings, such as hospitals and long-term care facilities, and can lead to more severe, life-threatening infections.

What are the common symptoms and health impacts of Methicillin-Resistant infections?

Methicillin-Resistant infections can cause a range of symptoms and health impacts, depending on the type of infection and the severity. Common symptoms include: - Skin and wound infections, such as boils, abscesses, or cellulitis - Pneumonia - Bloodstream infections - Surgical site infections - Sepsis, a life-threatening condition caused by the body's extreme response to an infection Untreated or severe Methicillin-Resistant infections can lead to serious complications, including organ failure, limb amputation, and even death. Prompt diagnosis and appropriate treatment are crucial for managing these infections.

How can PubCompare.ai assist in Methicillin-Resistant research and management?

PubCompare.ai can be a valuable tool for researchers and healthcare professionals working with Methicillin-Resistant. The platform allows you to: 1. Screen protocol literature more efficiently: PubCompare.ai's AI-powered search and analysis tools can help you quickly identify the most relevant and up-to-date protocols related to Methicillin-Resistant from a wide range of sources, including published literature, preprints, and patents. 2. Leverage AI to pinpoint critical insights: The platform's advanced AI algorithms can analyze protocol details, highlighting key differences in effectiveness, reproducibility, and accuracy. This can help you make more informed decisions about the best protocols to use for your Methicillin-Resistant studies and management strategies. By using PubCompare.ai, you can save time, improve the quality of your research, and ultimately contribute to the development of more effective treatments and strategies for managing this significant public health concern.

More about "Methicillin-Resistant"

Methicillin-Resistant Staphylococcus aureus (MRSA) is a type of antibiotic-resistant bacteria that has become a significant public health concern.
This gram-positive cocci is a strain of Staphylococcus aureus that has developed resistance to the antibiotic methicillin and other related antibiotics, such as oxacillin, making it more difficult to treat.
MRSA can cause a wide range of illnesses, from mild skin and wound infections to more severe and life-threatening conditions, including pneumonia, sepsis, and endocarditis.
Identifying effective protocols and strategies is crucial for researching and managing MRSA.
PubCompare.ai, an AI-powered protocol comparison tool, can revolutionize MRSA research by helping researchers locate the best protocols from literature, preprints, and patents using advanced AI algorithms.
This user-friendly interface allows researchers to easily identify the optimal products and strategies for their MRSA studies, accelerating the development of new treatments and management approaches.
In addition to MRSA, other antibiotic-resistant bacteria, such as Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Candida albicans, pose significant challenges in healthcare settings.
Effective protocols and strategies for managing these pathogens are also essential to address the growing threat of antimicrobial resistance.
Techniques like Mueller-Hinton broth, ATCC 43300, and Vitek 2 can be valuable tools in identifying and characterizing these resistant strains.
By leveraging the insights from PubCompare.ai and incorporating the latest research on antibiotic-resistant bacteria, researchers and healthcare professionals can enhance their understanding of MRSA and develop more effective strategies for its prevention and treatment, ultimately improving patient outcomes and reducing the burden of this significant public health concern.