Exploration of Clinical Breakpoint of Danofloxacin for Glaesserella parasuis in Plasma and in PELF
Abstract
:1. Introduction
2. Materials and Methods
2.1. Strains
2.2. Animals
2.3. Establishment of ECV
2.4. Establishment of COPD Based on PK-PD Modeling
2.4.1. Selection of Pathogenic G. parasuis
2.4.2. Pharmacodynamics In Vitro and Ex-Vivo
2.4.3. Animal Experiment and Sample Collection for Pharmacokinetics Study
2.4.4. Quantitation Analysis of Danofloxacin by HPLC
2.4.5. Pharmacokinetics-Pharmacodynamics Modeling
2.4.6. Monte Carlo Simulation to Set up COPD
2.5. Clinical Trial and Establishment of COCL
2.5.1. Infection Model and Clinical Trials
2.5.2. Statistical Analysis for Establishment of COCL
3. Results
3.1. ECV for Danofloxacin against G. parasuis
3.2. COPD for Danofloxacin against G. parasuis
3.2.1. Pathogenic G. parasuis
3.2.2. Pharmacodynamics of Danofloxacin against G. parasuis
3.2.3. Sensitivity and Accuracy of HPLC Method for Determination of Danofloxacin
3.2.4. PK Characteristics of Danofloxacin in Plasma and PELF
3.2.5. Monte Carlo Simulation and COPD
3.3. COCL of Danofloxacin against G. parasuis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Oliveira, S.; Pijoan, C. Haemophilus parasuis: New trends on diagnosis, epidemiology and control. Vet. Microbiol. 2004, 99, 1–12. [Google Scholar] [CrossRef] [PubMed]
- Kielstein, P.; Rapp-Gabrielson, V.J. Designation of 15 serovars of Haemophilus parasuis on the basis of immunodiffusion using heat-stable antigen extracts. J. Clin. Microbiol. 1992, 30, 862–865. [Google Scholar] [CrossRef] [Green Version]
- Cai, X.; Chen, H.; Blackall, P.J.; Yin, Z.; Lei, W.; Liu, Z.; Jin, M. Serological characterization of Haemophilus parasuis isolates from China. Vet. Microbiol. 2005, 111, 231–236. [Google Scholar] [CrossRef]
- Nedbalcova, K.; Zouharova, M.; Sperling, D. The determination of minimum inhibitory concentrations of selected antimicrobials for porcine Haemophilus parasuis isolates from the Czech Republic. Acta Vet. Brno 2017, 86, 175–181. [Google Scholar] [CrossRef]
- Drlica, K.; Zhao, X.L. DNA Gyrase, Topoisomerase IV, and the 4Quinolones. Microbiol. Mol. Biol. Rev. 1997, 61, 377–392. [Google Scholar] [PubMed]
- Manzoor, Z.; Munawar, S.H.; Iqbal, Z. Pharmacokinetics and pharmacokinetic/pharmacodynamic integration of danofloxacin in Lohi sheep. Int. J. Infect. Dis. 2020, 101, 117. [Google Scholar] [CrossRef]
- Aliabadi, F.S.; Landoni, M.F.; Lees, P. Pharmacokinetics (PK), pharmacodynamics (PD), and PK-PD integration of danofloxacin in sheep biological fluids. Antimicrob. Agents Chemother. 2003, 47, 626–635. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cherif, K.T.; Peris-Vicente, J.; Carda-Broch, S.; Esteve-Romero, J. Analysis of danofloxacin, difloxacin, ciprofloxacin and sarafloxacin in honey using micellar liquid chromatography and validation according to the 2002/657/EC decision. Anal. Methods 2015, 7, 6165–6172. [Google Scholar] [CrossRef]
- Fernandez-Varon, E.; Marin, P.; Escudero, E.; Vancraeynest, D.; Cárceles, C.M. Pharmacokinetic-pharmacodynamic integration of danofloxacin after intravenous, intramuscular and subcutaneous administration to rabbits. J. Vet. Pharmacol. Ther. 2007, 30, 18–24. [Google Scholar] [CrossRef]
- Haritova, A.M.; Rusenova, N.V.; Parvanov, P.R.; Lashev, L.D.; Fink-Gremmels, J. Pharmacokinetic-pharmacodynamic modelling of danofloxacin in turkeys. Vet. Res. Commun. 2006, 30, 775–789. [Google Scholar] [CrossRef]
- Mann, D.D.; Frame, G.M. Pharmacokinetic study of danofloxacin in cattle and swine. Am. J. Vet. Res. 1992, 53, 1022–1026. [Google Scholar]
- Toutain, P.L.; Bousquet-Mélou, A.; Damborg, P.; Ferran, A.A.; Mevius, D.; Pelligand, L.; Veldman, K.T.; Lees, P. En Route towards European Clinical Breakpoints for Veterinary Antimicrobial Susceptibility Testing: A Position Paper Explaining the VetCAST Approach. Front. Microbiol. 2017, 8, 2344. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Turnidge, J.; Kahlmeter, G.; Kronvall, G. Statistical characterisation of bacterial wild-type MIC value distributions and the determination of epidemiological cut-off values. Clin. Microbiol. Infect. 2006, 12, 418–425. [Google Scholar] [CrossRef]
- Kronvall, G. Normalized Resistance Interpretation as a Tool for Establishing Epidemiological MIC Susceptibility Breakpoints. J. Clin. Microbiol. 2010, 48, 4445–4452. [Google Scholar] [CrossRef] [Green Version]
- Canton, E.; Peman, J.; Hervas, D.; Iniguez, C.; Navarro, D.; Echeverria, J.; Martinez-Alarcon, J.; Fontanals, D.; Gomila-Sard, B.; Buendia, B. Comparison of Three Statistical Methods for Establishing Tentative Wild-Type Population and Epidemiological Cutoff Values for Echinocandins, Amphotericin B, Flucytosine, and Six Candida Species as Determined by the Colorimetric Sensititre YeastOne Method. J. Clin. Microbiol. 2012, 50, 3921–3926. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rey, J.E.; Laffont, C.M.; Croubels, S.; Backer, P.D.; Zemirline, C.; Bousquet, E.; Guyonnet, J.; Ferran, A.A.; Bousquet-Melou, A.; Toutain, P.L. Use of Monte Carlo simulation to determine pharmacodynamic cutoffs of amoxicillin to establish a breakpoint for antimicrobial susceptibility testing in pigs. Am. J. Vet. Res. 2014, 75, 124–131. [Google Scholar] [CrossRef] [Green Version]
- Turnidge, J.D.; Martinez, M.N. Proposed method for estimating clinical cut-off (COCL) values: An attempt to address challenges encountered when setting clinical breakpoints for veterinary antimicrobial agents. Vet. J. 2017, 228, 33–37. [Google Scholar] [CrossRef] [PubMed]
- Oliveira, S.; Galina, L.; Pijoan, C. Development of a PCR test to diagnose Haemophilus parasuis infections. J. Vet. Diagn Investig. 2001, 13, 495–501. [Google Scholar] [CrossRef] [Green Version]
- Ferraro, M.J. Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria That Grow Aerobically; Clinical and Laboratory Standards Institute: Annapolis Junction, MD, USA, 2000; pp. 24–25. [Google Scholar]
- Espinel-Ingroff, A.; Turnidge, J.; Alastruey-Izquierdo, A.; Dannaoui, E.; Tortorano, A.M. Posaconazole MIC distributions for Aspergillus fumigatus SC by four methods: Impact of Cyp51A mutations on estimation of epidemiological cutoff values (ECVs/ECOFFs). Antimicrob. Agents Chemother. 2018, 62, e01916-17. [Google Scholar] [CrossRef] [Green Version]
- Rafiee, M.; Bara, M.; Stephens, C.P.; Blackall, P.J. Application of ERIC-PCR for the comparison of isolates of Haemophilus parasuis. Aust. Vet. J. 2000, 78, 846–849. [Google Scholar] [CrossRef] [Green Version]
- Versalovic, J.; Koeuth, T.; Lupski, J.R. Distribution of repetitive DNA sequences in eubacteria and application to fingerprinting of bacterial genomes. Nucleic Acids Res. 1991, 19, 6823–6831. [Google Scholar] [CrossRef] [PubMed]
- Yu, J.; Zhang, Y.Y.; Du, Y.J.; Li, J.; Huang, B.H.; Sun, W.B.; Cong, X.Y.; Peng, J.; Ren, S.F.; Gou, L.H.; et al. The BALB/c mouse infection model for improving the Haemophilus parasuis serotyping scheme. Res. Vet. Sci. 2016, 109, 166–168. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.H.; Li, Y.; Dai, K.; Wen, X.T.; Wu, R.; Huang, X.B.; Jin, J.; Xu, K.; Yan, Q.G.; Huang, Y.; et al. Establishment of a Successive Markerless Mutation System in Haemophilus parasuis through Natural Transformation. PLoS ONE 2015, 10, e0127393. [Google Scholar] [CrossRef]
- Giguere, S.; Huang, R.; Malinski, T.J.; Dorr, P.M.; Tessman, R.K.; Somerville, B.A. Disposition of gamithromycin in plasma, pulmonary epithelial lining fluid, bronchoalveolar cells, and lung tissue in cattle. Am. J. Vet. Res. 2011, 72, 326–330. [Google Scholar] [CrossRef]
- Kiem, S.; Schentag, J.J. Interpretation of antibiotic concentration ratios measured in epithelial lining fluid. Antimicrob. Agents Chemother. 2008, 52, 24–36. [Google Scholar] [CrossRef] [Green Version]
- Conte, J.E., Jr.; Golden, J.A.; McQuitty, M.; Kipps, J.; Lin, E.T.; Zurlinden, E. Effects of AIDS and gender on steady-state plasma and intrapulmonary ethionamide concentrations. Antimicrob. Agents Chemother. 2000, 44, 1337–1341. [Google Scholar] [CrossRef] [Green Version]
- Mouton, J.W. Breakpoints: Current practice and future perspectives. Int. J. Antimicrob. Agents 2002, 19, 323–331. [Google Scholar] [CrossRef]
- Xiao, X.; Sun, J.; Chen, Y.; Huang, R.J.; Huang, T.; Qiao, G.G.; Zhou, Y.F.; Liu, Y.H. In Vitro dynamic pharmacokinetic/pharmacodynamic (PK/PD) modeling and PK/PD cutoff of cefquinome against Haemophilus parasuis. BMC Vet. Res. 2015, 11, 33. [Google Scholar] [CrossRef] [Green Version]
- Potter, T.; Illambas, J.; Pelligand, L.; Rycroft, A.; Lees, P. Pharmacokinetic and pharmacodynamic integration and modelling of marbofloxacin in calves for Mannheimia haemolytica and Pasteurella multocida. Vet. J. 2013, 195, 53–58. [Google Scholar] [CrossRef] [PubMed]
- Sidhu, P.; Rassouli, A.; Illambas, J.; Potter, T.; Pelligand, L.; Rycroft, A.; Lees, P. Pharmacokinetic-pharmacodynamic integration and modelling of florfenicol in calves. J. Vet. Pharm. 2014, 37, 231–242. [Google Scholar] [CrossRef]
- Toutain, P.L.; Del Castillo, J.R.E.; Bousquet-Melou, A. The pharmacokinetic-pharmacodynamic approach to a rational dosage regimen for antibiotics. Res. Vet. Sci. 2002, 73, 105–114. [Google Scholar] [CrossRef]
- Aarestrup, F.M.; Seyfarth, A.M.; Angen, O. Antimicrobial susceptibility of Haemophilus parasuis and Histophilus somni from pigs and cattle in Denmark. Vet. Microbiol. 2004, 101, 143–146. [Google Scholar] [CrossRef]
- De la Fuente, A.J.; Tucker, A.W.; Navas, J.; Blanco, M.; Morris, S.J.; Gutierrez-Martin, C.B. Antimicrobial susceptibility patterns of Haemophilus parasuis from pigs in the United Kingdom and Spain. Vet. Microbiol. 2007, 120, 184–191. [Google Scholar] [CrossRef] [Green Version]
- Zhou, X.; Xu, X.J.; Zhao, Y.X.; Chen, P.; Zhang, X.; Chen, H.C.; Cai, X.W. Distribution of antimicrobial resistance among different serovars of Haemophilus parasuis isolates. Vet. Microbiol. 2010, 141, 168–173. [Google Scholar] [CrossRef]
- Xu, C.; Zhang, J.M.; Zhao, Z.Q.; Guo, L.L.; Zhang, B.; Feng, S.X.; Zhang, L.Y.; Liao, M. Antimicrobial susceptibility and PFGE genotyping of Haemophilus parasuis isolates from pigs in South China (2008–2010). J. Vet. Med. Sci. 2011, 73, 1061–1065. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, Z.H.; Zhao, Q.; Wei, H.L.; Wen, X.T.; Cao, S.J.; Huang, X.B.; Wu, R.; Yan, Q.G.; Huang, Y.; Wen, Y.P. Prevalence and seroepidemiology of Haemophilus parasuis in Sichuan province. China PeerJ 2017, 5, e3379. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sun, J.; Xiao, X.; Huang, R.J.; Yang, T.; Chen, Y.; Fang, X.; Huang, T.; Zhou, Y.F.; Liu, Y.H. In vitro Dynamic Pharmacokinetic/Pharmacodynamic (PK/PD) study and COPD of Marbofloxacin against Haemophilus parasuis. BMC Vet. Res. 2015, 11, 293. [Google Scholar] [CrossRef] [PubMed]
- Zhang, P.; Hao, H.H.; Li, J.; Ahmad, I.; Cheng, G.Y.; Chen, D.M.; Tao, Y.F.; Huang, L.L.; Wang, Y.L.; Dai, M.H. The Epidemiologic and Pharmacodynamic Cutoff Values of Tilmicosin against Haemophilus parasuis. Front. Microbiol. 2016, 7, 385. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lauritzen, B.; Lykkesfeldt, J.; Friis, C. Evaluation of a single dose versus a divided dose regimen of danofloxacin in treatment of Actinobacillus pleuropneumoniae infection in pigs. Res. Vet. Sci. 2003, 74, 271–277. [Google Scholar] [CrossRef]
- Zeng, Z.; Deng, G.; Shen, X.; Rizwan-ul-Haq, M.; Zeng, D.; Ding, H. Plasma and tissue pharmacokinetics of danofloxacin in healthy and in experimentally infected chickens with Pasteurella multocida. J. Vet. Pharm. 2011, 34, 101–104. [Google Scholar] [CrossRef]
- Fajt, V.R.; Apley, M.D.; Brogden, K.A.; Skogerboe, T.L.; Shostrom, V.K.; Chin, Y.L. Effect of danofloxacin and tilmicosin on body temperatures of beef calves with pneumonia experimentally induced by inoculation with Mannheimia haemolytica. Am. J. Vet. Res. 2004, 65, 610–615. [Google Scholar] [CrossRef] [PubMed]
- Kronvall, G.; Karlsson, I.; Walder, M.; Sorberg, M.; Nilsson, L.E. Epidemiological MIC cut-off values for tigecycline calculated from Etest MIC values using normalized resistance interpretation. J. Antimicrob. Chemother. 2006, 57, 498–505. [Google Scholar] [CrossRef] [PubMed]
- Ismail, N.A.; Omar, S.V.; Joseph, L.; Govender, N.; Blows, L.; Ismail, F.; Koornhof, H.; Dreyer, A.W.; Kaniga, K.; Ndjeka, N. Defining Bedaquiline Susceptibility, Resistance, Cross-Resistance and Associated Genetic Determinants: A Retrospective Cohort Study. EBioMedicine 2018, 28, 136–142. [Google Scholar] [CrossRef] [Green Version]
- Van Vliet, D.; Loch, T.P.; Smith, P.; Faisal, M. Antimicrobial Susceptibilities of Flavobacterium psychrophilum Isolates from the Great Lakes Basin, Michigan. Microb. Drug Resist. 2017, 23, 791–798. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Q.; Zhou, M.G.; Song, D.S.; Zhao, J.P.; Zhang, A.D.; Jin, M.L. Molecular characterisation of resistance to fluoroquinolones in Haemophilus parasuis isolated from China. Int. J. Antimicrob. Agents 2013, 42, 87–89. [Google Scholar] [CrossRef]
- Barbour, A.; Scaglione, F.; Derendorf, H. Class-dependent relevance of tissue distribution in the interpretation of anti-infective pharmacokinetic/pharmacodynamic indices. Int. J. Antimicrob. Agents 2010, 35, 431–438. [Google Scholar] [CrossRef]
- Yang, Y.; Zhang, Y.X.; Li, J.R.; Cheng, P.; Xiao, T.S.; Muhammad, I.; Yu, H.X.; Liu, R.M.; Zhang, X.Y. Susceptibility breakpoint for Danofloxacin against swine Escherichia coli. BMC Vet. Res. 2019, 15, 51. [Google Scholar] [CrossRef]
- Rowan, T.G.; Sarasola, P.; Sunderland, S.J.; Giles, C.J.; Smith, D.G. Efficacy of danofloxacin in the treatment of respiratory disease in European cattle. Vet. Rec. 2004, 154, 585–589. [Google Scholar] [CrossRef]
- Toutain, P.L. Setting clinical breakpoint Methodological aspects. European Committee on Antimicrobial Susceptibility Testing. France. 2015. Available online: https://eucast.org/ast_of_veterinary_pathogens/ (accessed on 30 April 2021).
- Esterly, J.S.; Wagner, J.; McLaughlin, M.M.; Postelnick, M.J.; Qi, C.; Scheetz, M.H. Evaluation of Clinical Outcomes in Patients with Bloodstream Infections Due to Gram-Negative Bacteria According to Carbapenem MIC Stratification. Antimicrob. Agents Chemother. 2012, 56, 4885–4890. [Google Scholar] [CrossRef] [Green Version]
- Zheng, X.; Zheng, R.R.; Hu, Y.; Werngren, J.; Forsman, L.D.; Mansjo, M.; Xu, B.; Hoffner, S. Determination of MIC Breakpoints for Second-Line Drugs Associated with Clinical Outcomes in Multidrug-Resistant Tuberculosis Treatment in China. Antimicrob. Agents Chemother. 2016, 60, 4786–4792. [Google Scholar] [CrossRef] [Green Version]
- Bhat, S.V.; Peleg, A.Y.; Lodise, T.P.; Shutt, K.A.; Capitano, B.; Potoski, B.A.; Paterson, D.L. Failure of current cefepime breakpoints to predict clinical outcomes of bacteremia caused by gram-negative organisms. Antimicrob. Agents Chemother. 2007, 51, 4390–4395. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cuesta, I.; Bielza, C.; Cuenca-Estrella, M.; Larranaga, P.; Rodriguez-Tudela, J.L. Evaluation by data mining techniques of fluconazole breakpoints established by the Clinical and Laboratory Standards Institute (CLSI) and comparison with those of the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Antimicrob. Agents Chemother. 2010, 54, 1541–1546. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sweeney, M.T.; Papich, M.G.; Watts, J.L. New interpretive criteria for danofloxacin antibacterial susceptibility testing against Mannheimia haemolytica and Pasteurella multocida associated with bovine respiratory disease. J. Vet. Diagn Investig. 2017, 29, 224–227. [Google Scholar] [CrossRef] [PubMed]
- Guo, L.; Zhang, J.M.; Xu, C.G.; Zhao, Y.D.; Ren, T.; Zhang, B.; Fan, H.Y.; Liao, M. Molecular characterization of fluoroquinolone resistance in Haemophilus parasuis isolated from pigs in South China. J. Antimicrob. Chemother. 2011, 66, 539–542. [Google Scholar] [CrossRef] [Green Version]
Parameters | Unit | Plasma | PELF |
---|---|---|---|
A | μg/mL | 0.43 ± 0.16 | 6.50 ± 2.21 |
B | μg/mL | 0.37 ± 0.18 | 0.54 ± 0.40 |
α | 1/h | 0.40 ± 0.13 | 0.29 ± 0.04 |
β | 1/h | 0.14 ± 0.02 | 0.06 ± 0.02 |
K01 | 1/h | 25.04 ± 32.21 | 1.41 ± 0.50 |
K10 | 1/h | 0.13 ± 0.03 | 0.10 ± 0.85 |
K12 | 1/h | 0.12 ± 0.04 | 0.17 ± 0.78 |
K21 | 1/h | 0.13 ± 0.10 | 0.02 ± 0.18 |
T1/2K01 | h | 0.03 ± 0.03 | 0.49 ± 0.17 |
T1/2α | h | 1.78 ± 0.76 | 2.39 ± 0.3 |
T1/2β | h | 4.96 ± 0.47 | 10.46 ± 0.76 |
Tmax | h | 0.23 ± 0.07 | 1.61 ± 0.15 |
AUC24 | h·μg/mL | 4.47 ± 0.51 | 24.28 ± 2.70 |
Cmax | μg/mL | 0.67 ± 0.01 | 3.67 ± 0.25 |
CL/F | mL/h/kg | 571.49 ± 53.02 | 89.98 ± 9.7 |
Vd/F | mL/kg | 3531.73 ± 49.12 | 435.04 ± 45.43 |
Time (h) | Cvivo | (AUIC)ex | E (logCFU/mL) | Calculated PD Target |
---|---|---|---|---|
0 | 0.00 | 0.00 | 3.62 | E0 = 3.62 PDmax = 8.67 EC50 = 15.24 γ = 1.85 AUIC (E = 0) = 12.73 AUIC (E = −3) = 28.68 AUIC (E = −4) = 44.38 |
0.5 | 2.11 ± 0.37 | 25.34 ± 4.39 | −3.12 | |
1 | 3.13 ± 0.35 | 37.54 ± 4.21 | −5.05 | |
1.5 | 3.89 ± 0.11 | 46.70 ± 1.37 | −5.05 | |
2 | 3.51 ± 0.33 | 42.15 ± 3.96 | −5.05 | |
3 | 3.02 ± 0.21 | 36.28 ± 2.53 | −5.05 | |
4 | 2.23 ± 0.25 | 26.81 ± 2.95 | −3.59 | |
6 | 1.56 ± 0.45 | 18.72 ± 5.39 | −1.84 | |
8 | 1.02 ± 0.23 | 12.28 ± 2.75 | −1.07 | |
10 | 0.69 ± 0.19 | 8.31 ± 2.33 | 1.49 | |
12 | 0.38 ± 0.16 | 4.56 ± 1.90 | 3.24 | |
24 | 0.27 ± 0.03 | 3.24 ± 0.31 | 3.34 |
MIC (μg/mL) | PELF | Plasma | ||||
---|---|---|---|---|---|---|
PTA% (E = 0) | PTA% (E = −3) | PTA% (E = −4) | PTA% (E = 0) | PTA% (E = −3) | PTA% (E = −4) | |
0.015 | 100 | 100 | 100 | 100 | 100 | 100 |
0.03 | 100 | 100 | 100 | 100 | 100 | 100 |
0.125 | 100 | 100 | 100 | 100 | 98.46 | 1.24 |
0.25 | 100 | 100 | 100 | 99.94 | 0 | 0 |
0.5 | 100 | 100 | 80.97 | 0.04 | 0 | 0 |
1 | 100 | 3.81 | 0 | 0 | 0 | 0 |
2 | 29.95 | 0 | 0 | 0 | 0 | 0 |
4 | 0 | 0 | 0 | 0 | 0 | 0 |
8 | 0 | 0 | 0 | 0 | 0 | 0 |
16 | 0 | 0 | 0 | 0 | 0 | 0 |
32 | 0 | 0 | 0 | 0 | 0 | 0 |
Strain Number | Strain Group | MIC (μg/mL) | Success (%) | Eradication (%) | POC (%) | MaxDiff | CAR |
---|---|---|---|---|---|---|---|
H42 | Test | 16 | 67.7 | 67.7 | 67.7 | 0 | 0.70 |
Control | 16.7 | 0 | 0 | ||||
H80 | Test | 4 | 67.7 | 83.3 | 67.7 | 0 | 0.79 |
Control | 33.3 | 16.7 | 33.3 | ||||
H12 | Test | 1 | 83.3 | 83.3 | 83.3 | 0.167 | 0.93 |
Control | 33.3 | 16.7 | 33.3 | ||||
H83 | Test | 0.125 | 100 | 100 | 100 | 0.28 | 1 |
Control | 33.3 | 16.7 | 16.7 | ||||
H17 | Test | 0.015 | 100 | 100 | 100 | 0.21 | 1 |
Control | 50 | 33.3 | 33.3 |
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Xu, Z.; Huang, A.; Luo, X.; Zhang, P.; Huang, L.; Wang, X.; Mi, K.; Fang, S.; Huang, X.; Li, J.; et al. Exploration of Clinical Breakpoint of Danofloxacin for Glaesserella parasuis in Plasma and in PELF. Antibiotics 2021, 10, 808. https://doi.org/10.3390/antibiotics10070808
Xu Z, Huang A, Luo X, Zhang P, Huang L, Wang X, Mi K, Fang S, Huang X, Li J, et al. Exploration of Clinical Breakpoint of Danofloxacin for Glaesserella parasuis in Plasma and in PELF. Antibiotics. 2021; 10(7):808. https://doi.org/10.3390/antibiotics10070808
Chicago/Turabian StyleXu, Zihui, Anxiong Huang, Xun Luo, Peng Zhang, Lingli Huang, Xu Wang, Kun Mi, Shiwei Fang, Xiao Huang, Jun Li, and et al. 2021. "Exploration of Clinical Breakpoint of Danofloxacin for Glaesserella parasuis in Plasma and in PELF" Antibiotics 10, no. 7: 808. https://doi.org/10.3390/antibiotics10070808
APA StyleXu, Z., Huang, A., Luo, X., Zhang, P., Huang, L., Wang, X., Mi, K., Fang, S., Huang, X., Li, J., Yuan, Z., & Hao, H. (2021). Exploration of Clinical Breakpoint of Danofloxacin for Glaesserella parasuis in Plasma and in PELF. Antibiotics, 10(7), 808. https://doi.org/10.3390/antibiotics10070808