INTRODUCTION:

Many clinical microbiology laboratories use the agar disk-diffusion test, established in 1944 by Heatley¹, to determine antibiotic susceptibility. Clinical and Laboratory Standards Institute (CLSI) provides standards for testing bacteria and yeasts. This method is only suited for testing a subset of fastidious bacterial pathogens ^2,3. This procedure includes inoculating agar plates with the bacterium. The test material is then spotted on agar using filter paper discs (about 6mm in diameter).

Petri dishes are heated and humidified. Antimicrobial agents distributed into agar reduce microorganism germination and proliferation. Next, the growth medium, temperature, incubation duration, and inoculum size required by CLSI are measured. Anti-biogram classifies bacteria as sensitive, intermediate, or resistant. Its findings assist physicians pick the appropriate drugs for their patients, both initially and long-term⁴.

This technique cannot discriminate between bactericidal and bacteriostatic effects because bacterial growth inhibition is not equivalent with bacterial death⁵. Agar-disk diffusion is used in clinical laboratories to evaluate which antibiotics will treat infections best. Kirby–Bauer, 6mm disk diffusion over thick Mueller–Hinton agar is a typical experiment in solid mediums⁶. An inhibitory zone forms when antimicrobial agent is spread over a bacterial-infested plate. Insufficient anti-biomicrobial agent concentration marks the zone's edge. CLSI recommends categorizing a strain's medication susceptibility depending on the size of the zone surrounding it^2,7. This technique produces interpretative categories, per the description. Solid-medium tests are simple and inexpensive. Standard operating procedures improve the accuracy of manual agar-disk diffusion testing. Even a little change may affect the result. Other aspects that might affect results are commonly disregarded, such as bacterial growth rate and agent diffusion qualities. Considerations include resistant strains of bacteria in clinical settings and drug testing on these germs⁸, inoculum dose and storage⁹, disc alignment¹⁰, materials, and media^11,12. When considering medium and components, agar thickness seems most relevant. Alternate 4 mm layers of conventional and cation-adjusted Mueller Hinton agar for diffusion testing ^2,13. Davis and Stout¹¹ demonstrate that the amount of agar poured, the shape of the agar, the bottom shape of the plates and many plates are in the stack and where they are in relation to each other affect the accuracy. Woolfrey et al.¹² noted that Petri dish concavity affects accuracy. Hypothesis: Agar thickness and moisture alter antimicrobial drug diffusion, therefore affecting the zone of inhibition. For testing, use quantitative gradient diffusion. How well an antibiotic solution inhibits a microorganism or its products reveals its activity and, by extension, its concentration. Abrahams et al. (1941)¹⁴ and Tabaqchali et al. (1979)¹⁵ devised the "oxford cup" technique, which Heatley (1944) ¹ reported for penicillin and Soad Zuhair et al. (1979) ¹⁵ for cefoxitin. Grove, Randall (1955) ¹⁶, and Zuhair ¹⁷ invented the "steel cup." "Eight queens puzzle’’ " provided tens of various designs. Zuhair et al. (1972). Most models are built on prior methodologies to allow for 64 disks of evaluated samples^18–21. Our research involved two main parts. First, we used agar-disks diffusion on a transparent 32x32 cm larger plate for microbiological assay with lid to test a larger number of samples (up to 64 disks or holes). Second, we used a novel method to ensure that all of the samples were distributed evenly. This was accomplished by adapting the distribution principle used in the classic "eight queens puzzle" (5x5cm) to account for the larger sample size.

Figure 1. Photograph of the large plate and cover glass, simultaneously.

MATERIAL AND METHODS:

Plates will need to be prepared, and then poured. A large piece of plate glass measuring 13 inches by 13 inches (32.9 centimeters by 32.9 centimeters) is used for the assay plate. The distance between the plate glass and the flat surface varies according to the thickness of the medium being tested and is approximately 0.03, 0.07, 0.15, 0.23, and 0.31 inches (0.1, 0.2, 0.4, 0.6, and 0.8 centimeters). This allows for the creation of up to 64 uniform replications (Fig. 1). Epoxy glue is used to adhere the glass sides to the surface, with the sides projecting an additional 1 inch (2.5cm) above the surface. After that, a glass cover with a thickness of 0.25 inches may be firmly put over the top of the plate, and the seam can be sealed to prevent the plate from drying out. 11 inches is the diameter that may be found on the inside of the plate (27.9 by 27.9cm). After a thorough cleaning with soap and water, the glass is often prepared by swabbing it with an alcohol solution that is 70 percent ethyl and contains 4 percent concentrated HCI by volume. Additionally, the interior surface of the glass is swabbed with acetone and flamed before it is put to use. It is also possible to do autoclaving using flowing steam at a temperature of 100 degrees Celsius that is not under pressure, provided that the cooling of the glass is let to take place in a very progressive manner.

The assay agar is made by dispensing the medium from a large flask into six smaller flasks after mixing 76 grams of powder (Oxoid Muller Hinton agar) with 2,000 milliliters of distilled water in a large flask. The large flask is then placed in a water bath containing boiling water until the medium is clear (200ml each). As a result of the autoclaving process, there is about 125milliliters left when there were originally 145milliliters. Following the process of sterilizing, flasks that contain molten agar in the following volumes: 125, 250, 375, 500, and 625ml are put in a water bath heated to 56 degrees Celsius in order to keep the agar in a liquid form until it is emptied. Pouring (125, 250, 375, 500, 625ml) of seeded agar (see the section on Assay organisms for more information) into an assay plate that is placed on a particular pouring surface yields a layer that is about (1, 2, 4, 6, 8mm) deep and is uniform throughout its whole.After the seeded agar has had time to set, disks with a diameter of 6.0 millimeters are produced and deposited (Fig. 1). Because the thickness of the agar is 1, 2, 4, 6, and 8 millimeters, the concentrations of the various antibiotics are arranged in a symmetrical fashion. Even with varying antibiotic doses, the zone of inhibition provides adequate zone sizes, and they were chosen for the simplicity with which the Kirby Bauer Disc Diffusion technique may be carried out in accordance with CLSI Standard^11,12. Between October 2020 and February 2022, a retrospective study was performed in a tertiary care hospital in the city of Karbala. Iraq's Al-Hussein Medical City. The diagnostic work is carried out by the microbiology laboratory inside the pharmacy department of Al Zahrawi University College. S. aureus and E.coli were identified based on the morphology of the Gram’s stain procedure, the features of the colonies, and the results of positive tests for catalase and coagulase of S. aureus and API 20 test of E. coli, it was established that S. aureus and E. coli bacteria were both present in the sample relatively^12,22–25. Various clinical samples were isolated from inpatients, including sputum, urine, blood, cervical swab, and the tip of a catheter. The disc diffusion technique suggested by the Clinical and Laboratory Standard Institute was used to test for various antibiotics^12,26,27. The antibiogram was carried out using a modified version of the Kirby-Bauer Disc Diffusion technique in accordance with CLSI Standards against the following antibiotics: erythromycin (ERY) (10g), ceftriaxone (CRO) (10g), ciprofloxacin (CIP) (10 g), gentamicin (CN) (10g), and streptomycin (S) (25g).

RESULT:

As was the case in earlier research, zoi's were connected with agar thickness, and then ETESTs were used to make a comparison between zoi's and agar thickness. This was done so that the effects of varying agar depth could be examined and analyzed. It was possible to examine the effect of agar thickness on zoi in a more precise manner because to the quantitative data acquired using ETESTs. In this study, a clinical strain was utilized to investigate the effects of the antibiotics erythromycin (ERY), ceftriaxone (CRO), ciprofloxacin (CIP), gentamicin (CN), and streptomycin (S). The following levels of Mueller–Hinton agar (Oxoid, UK) were used for the experiment: 1, 2, 4, 6, and 8 millimeters. In the experiment, the quantity of agar required was calculated using the weight of the agar-filled plates [the weight of the empty plates changed by less than 0.3 percent (12.56± 0.033 g)]. On the day when the inoculation was performed, plate depth measurements were collected. The findings are presented in (Table 1, 2). When the depth of the agar plate is increased, the size of the zone of inhibition will also grow, but it will be smaller. This holds true for both ciprofloxacin and erythromycin. Ceftriaxone and gentamicin had an impact that was somewhere in the middle, with streptomycin showing the least amount of activity. The influence of solidifying on zone size was investigated by doing AST testing on plates with thicknesses of 1, 2, 4, 6, and 8 millimeters after the plates had been unstacked and left closed on the workbench for seven days. The values of agar depth and zoi that are provided in Tables 1 and 2 are compared with those that are provided in Tables 3 and 4 correspondingly for both types of bacteria, and the results reveal that zoi has a positive correlation with plate weight. Through the use of linear regression analysis, a model of the link between agar depth and zoi may be created. Between the agar depth and the zone of inhibition, there is always an inclination in the opposite direction. Ciprofloxacin has a steeper slope than either erythromycin or ceftriaxone, indicating a difference in the absolute slope between the different antibiotics. As the agar depth increases, the antimicrobial agent's agar diffusion coefficient is likely to have an impact on the zoi. This is because the agar diffusion coefficient is measured in millimeters per second. Although we did not directly measure the diffusion coefficient, we did examine the molecular weight of the five antibiotics that were utilized in this investigation. Ciprofloxacin has a lower molecular weight (331.35g/mol) than streptomycin (581.57g/mol), which had the highest molecular weight.

Table 1: Comparing zone of inhibition for Staphylococcus aureus growth in different thickness of culture media. P values were reported by using Dunn's multiple comparisons test and significant differences were highlighted with yellow color.

Antibiotic disc	P value for agar thickness groups comparisons
Antibiotic disc	1 vs. 2	1 vs. 4	1 vs. 6	1 vs. 8	2 vs. 4	2 vs. 6	2 vs. 8	4 vs. 6	4 vs. 8	6 vs. 8
Erythromycin	> 0.9999	0.0592	< 0.0001	< 0.0001	0.7111	< 0.0001	< 0.0001	0.0321	0.0019	> 0.9999
Ceftriaxone	> 0.9999	0.0156	< 0.0001	< 0.0001	0.1920	< 0.0001	< 0.0001	0.2595	0.0064	> 0.9999
Ciprofloxacin	0.5697	> 0.9999	< 0.0001	< 0.0001	> 0.9999	0.0087	< 0.0001	0.0011	< 0.0001	> 0.9999
Gentamycin	0.5123	0.0597	0.0001	< 0.0001	> 0.9999	0.1455	< 0.0001	> 0.9999	0.0003	0.1226
Streptomycin	> 0.9999	0.3094	0.0002	< 0.0001	0.4931	0.0006	< 0.0001	0.3849	0.0003	0.3278

Table 2: Comparing zone of growth inhibition for Escherichia coli in various thickness of culture media. P values were generated by using Dunn's multiple comparisons test and significant differences were highlighted with yellow color.

Antibiotic disc	P value for agar thickness groups comparisons
Antibiotic disc	1 vs. 2	1 vs. 4	1 vs. 6	1 vs. 8	2 vs. 4	2 vs. 6	2 vs. 8	4 vs. 6	4 vs. 8	6 vs. 8
Erythromycin	> 0.9999	0.2442	0.0002	< 0.0001	> 0.9999	0.0175	< 0.0001	0.4784	0.0001	0.1765
Ceftriaxone	> 0.9999	0.0377	< 0.0001	< 0.0001	> 0.9999	0.0035	< 0.0001	0.4557	0.0044	> 0.9999
Ciprofloxacin	> 0.9999	> 0.9999	0.0003	< 0.0001	> 0.9999	< 0.0001	< 0.0001	0.0407	0.0001	> 0.9999
Gentamycin	> 0.9999	0.1776	< 0.0001	< 0.0001	0.7036	< 0.0001	< 0.0001	0.0539	0.0026	> 0.9999
Streptomycin	0.1165	0.0007	< 0.0001	< 0.0001	> 0.9999	0.0696	0.0556	> 0.9999	> 0.9999	> 0.9999

Table 3: Linear regression results summary for zone of growth inhibition for Staphylococcus aureus treated with several antibiotics in different agar thickness.

Antibiotic	Slope	Slope 95% confidence interval	R²
Erythromycin	-0.8815 ± 0.05003	-0.9812 to -0.7817	0.7992
Ceftriaxone	-0.6858 ± 0.04423	-0.7740 to -0.5976	0.7550
Ciprofloxacin	-0.8498 ± 0.06402	-0.9775 to -0.7222	0.6932
Gentamycin	-0.6058 ± 0.05024	-0.7059 to -0.5056	0.6508
Streptomycin	-0.6111 ± 0.04046	-0.6918 to -0.5304	0.7452

Table 4: Linear regression tabular summary for zone of inhibition for Escherichia coli growth as treated with several antibiotics and in different agar thickness.

Antibiotic	Slope	Slope 95% confidence interval	R²
Erythromycin	-0.6616 ± 0.05047	-0.7622 to -0.5609	0.6878
Ceftriaxone	-0.5278 ± 0.04239	-0.6123 to -0.4433	0.6653
Ciprofloxacin	-0.6172 ± 0.06212	-0.7411 to -0.4933	0.5586
Gentamycin	-0.8352 ± 0.06104	-0.9569 to -0.7135	0.7059
Streptomycin	-0.2591 ± 0.03545	-0.3298 to -0.1885	0.4066

Figure 1: Effect of agar thickness on zone of growth inhibition for Staphylococcus aureus produced by different antibiotic discs as seen in figure legends. N (groups number) = 5 with a replicate of 16 for each individual group, data are presented as mean ± standard deviation. P value for Kruskal-Wallis test is <0.0001.

Figure 2: Effect of agar thickness on zone of inhibition for Escherichia coli growth produced by different antibiotic discs as seen in figure legends. N (groups number) = 5 with a replicate of 16 for each individual group, data are presented as mean ± standard deviation. P value for Kruskal-Wallis test is <0.0001.

Figure 3: Line fitting by using linear regression to elaborate the relationship between agar thickness and zone of growth inhibition for Staphylococcus aureus treated with different antibiotic discs as seen in figure legends. N (groups number) = 5 and each individual group is represented by 16 replicates as mean ± standard deviation. P value for slope ≠ zero is <0.0001.

Figure 4: Line fitting by using linear regression to investigate the relation between agar thickness and zone of inhibition for Escherichia coli growth treated with several antibiotic discs as seen in figure legends. N (groups number) = 5 and each individual group is represented by 16 replicates as mean ± standard deviation. P value for slope ≠ zero is <0.0001.

DISCUSSION:

Its simplicity, low cost, ability to test large numbers of bacteria and antimicrobial medicines, and ease with which the results are interpreted make the agar-disks diffusion assay superior to other approaches. Moreover, several studies have shown that people with bacterial infections are eager to try an antibiotherapy tailored to their specific microbe's antibiogram^28,29. Plant extracts, essential oils, and other therapeutics are routinely subjected to antimicrobial screening because of the previously described advantages of this approach^30,31, especially its ease and cheap cost^32–36. The agar-disks diffusion method has been widely used for 50 years to determine whether or not bacteria are resistant to a certain drug. The cup technique³⁷ the paper disc method,³⁸ and the standardized single disc method (SSM) are all examples of its many iterations³⁹. Findings from zoi determinations utilizing these methods have been shown to be equivalent^25,40. Thickness and consistency of the agar, cut-off sizes for zoi and breakpoints, temperature, etc. all affect the reliability of the agar-disks diffusion method. When these potentially confounding aspects are addressed or taken into account, the interpretation of the results from an agar diffusion test is based on theoretical models that combine a range of other critical assumptions, although necessary for the usage of these theoretical models, also create certain restrictions to the models' validity, therefore it's crucial to be aware of them.

According to theoretical antibiotic diffusion studies, the hydrodynamic viscous drag is the limiting element in the diffusion of antibiotics⁴¹. The "Eight Queens Puzzle" is the most popular model¹⁹. Plates of 32x32 cm have replaced the traditional 25x25 cm size in a semi-infinite area^18,42 to accommodate larger test samples (up to 64 disks)²¹. The thickness of agar plates is related to the zoi factor in an equation⁴³ and there are a number of equations that may be used to determine the appropriate thickness of agar plates^44–46. This method facilitates reliable detection of antibiotic resistance, particularly to penicillins^41,47. This model provides a good match for the diffusion data we've collected for erythromycin, ceftriaxone, ciprofloxacin, gentamicin, and streptomycin.

Free agar diffusion model inadequately describes association between antibiotic concentration and inhibition zone size. Subtilin and tetracycline exhibit a linear relationship between zoi size and logarithm of concentration⁴⁸. Other models have been created because of problems with the free diffusion model. These models assume a quadratic relationship between zone size and concentration and use novel methods such as increasing the agar surface area by increasing the size of the plate^21,49–51. The first method is a straightforward method for determining the size of a well zone across a broad range of concentrations. The latter method needs an unending succession of special functions, which is impractical for routine microbiological work. Antibiotics may be lost owing to interactions with solid medium components, aggregation, or other processes. In our method, which is a novel way of distributing disks and its relationship with agar thickness, there are many potential solutions, including the development of antibiotic disks and a change in agar thickness. Two possible solutions: Logarithmic correlation between zone width and concentration is clearly described by free or dissipative models in most real situations, and the complex mathematical approach adds little. Change the thickness. In most cases, a mathematical approach adds little benefit. In addition, "eight queens puzzle" best reflected the connection of zone size on logarithm of concentration for all antibiotics evaluated for agar surface distribution. The free eight-queens puzzle model provides a very accurate description of antibiotic-induced zoi sizes, as shown by our investigations utilizing agar-diffusion in plate and their link with agar thickness. Linear regression was needed to determine the connection between agar thickness and zone of growth inhibition for Staphylococcus aureus and Escherichia coli treated with antibiotic discs. The first group (erythromycin) had similar outcomes for both bacteria (Fig. 3, 4), while the second group (gentamicin and ceftriaxone) had similar findings. Third group (ciprofloxacin) best suited linear model. With streptomycin, both bacteria showed the same residual deviation. The concentration dependence within the streptomycin group was even bigger than linear, suggesting that rather than a single concentration operating as a cut-off point, there is a range of values at which the test organism shows limited sensitivity to these antibiotics. Consideration of the mechanism through which antibiotics work is also relevant to this alternative hypothesis. Bacteriostatic antibiotics, like Erythromycin, halt the growth of bacteria rather than eradicating them instantly. The bacteria in the first group use an active transport mechanism to take up erythromycin.

This effect is achieved by impeding the process of protein synthesis. The 23S ribosomal RNA molecule, which is present in the 50S subunit of the ribosome in bacteria, binds to Erythromycin, preventing the peptide chain from leaving the ribosome^52–54. Gentamicin, which belongs to the second category, undergoes oxygen-dependent active transport when it crosses the membrane. Once in the cytoplasm, gentamicin and other aminoglycosides bind to the 16s rRNA at the 30s ribosomal subunit. This disrupts the translation of mRNA, which ultimately results in the creation of proteins that are either truncated or nonfunctional⁵⁵, In addition, ceftriaxone is effective because it blocks the production of mucopeptides in the bacterial cell wall. Ceftriaxone's beta-lactam component forms strong bonds with the carboxypeptidases, endopeptidases, and transpeptidases that are found in the cytoplasmic membrane of bacteria. These enzymes have a hand in the production of cell walls as well as the division of cells. The binding of ceftriaxone to these enzymes causes the enzyme to lose function, which in turn leads to the production of faulty cell walls by the bacteria, which ultimately results in the death of the cells⁵⁶. Ciprofloxacin, a fluoroquinolone antibiotic, is one of the three fluoroquinolones. It impedes DNA replication by interfering with the activity of bacterial DNA topoisomerase and DNA-gyrase, both of which are essential for DNA replication⁵⁷. Streptomycin inhibits ribosomal protein/peptide synthesis. It binds to 16S rRNA on the 30S component of the bacterial ribosome, limiting its activity and stopping protein synthesis by blocking peptide bond formation^58–60. Due to multidrug pumps and other considerations, the antibiotic concentration at the target may not match the concentration in a medium as represented by current diffusion models. Antibiotic dispersion in the medium has a minor impact, according to this text. Variables may affect agar diffusion experiment accuracy. Multiple discs are put on the same Petri plate for tests to eliminate growth time or temperature discrepancies. Agar homogeneity and thickness may alter zone size and shape, hence preparation is key¹¹. Eight queens puzzle model avoids antibiotic interactions, regardless of dose, hence agar distribution does not need to be precise.

CONCLUSION:

In order to assess the zone of inhibition in antimicrobial susceptibility testing, disk diffusion is frequently used on a solid medium. Previous research has shown that variations in agar depth may alter the reliability of this test^11,12, the recommended agar depth according to CLSI standards is 4 mm. Assay users have no idea how precise they need to be when pouring plates until they learn how variations in this depth impact findings. To measure the correlation between agar depth and zoi, we employed a novel modified approach for disk distribution and used data acquired from ETESTs. The smaller the agent under examination, the stronger the negative connection we observe between these two factors.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

REFERENCES:

1. Heatley NG. A Method For The Assay Of Penicillin. Biochemical Journal. 1944;38(1):61. doi.org/10.1042/bj0380061

2. Testing S. M100-S23 Performance Standards for Antimicrobial.; 2013. https://clsi.org/standards/products/microbiology/documents/m100/

3. CLSI C, Wayne PA. Method For Antifungal Disk Diffusion Susceptibility Testing Of Yeasts, Approved Guideline. CLSI document M44-A.[Google Scholar]. 2004.

4. Fiebelkorn KR, Crawford SA, Mcelmeel ML, Jorgensen JH. Practical Disk Diffusion Method For Detection Of Inducible Clindamycin Resistance In Staphylococcus Aureus And Coagulase-Negative StaphylococShow: 0 New Items - All Items Show: Items With Comments - All Shared Items Mark All As Read Refresh Feed Settings. Society. 2003;41(10):4740–4744. doi.org/10.1128/JCM.41.10.4740

5. Caron F. Antimicrobial Susceptibility Testing: A Four Facets Tool For The Clinician. Journal des anti-infectieux. 2012;14(4):168–174. doi.org/10.1016/j.antinf.2012.10.002

6. Hudzicki J. Kirby-Bauer Disk Diffusion Susceptibility Test Protocol. American society for microbiology. 2009;15:55–63.

7. Piddock LJ. Techniques Used For The Determination Of Antimicrobial Resistance And Sensitivity In Bacteria. Antimicrobial Agents Research Group. The Journal of applied bacteriology. 1990;68(4):307–318. doi.org/10.1111/j.1365-2672.1990.tb02880.x

8. Brennan-Krohn T, Smith KP, Kirby JE. The Poisoned Well: Enhancing The Predictive Value Of Antimicrobial Susceptibility Testing In The Era Of Multidrug Resistance. Journal of Clinical Microbiology. 2017;55(8):2304–2308. doi.org/10.1128/JCM.00511-17

9. Hombach M, Maurer FP, Pfiffner T, Böttger EC, Furrer R. Standardization Of Operator-Dependent Variables Affecting Precision And Accuracy Of The Disk Diffusion Method For Antibiotic Susceptibility Testing. Journal of clinical microbiology. 2015;53(12):3864–3869. doi.org/10.1128/JCM.02351-15

10. Cunningham DD, Flournoy DJ. The Relationship Of Disc Position To Zone-Of-Inhibition Size In The Disc-Agar Diffusion Test. Methods and Findings in Experimental and Clinical Pharmacology. 1983;5(2):101–105. https://pubmed.ncbi.nlm.nih.gov/6876941/

11. Davis WW, Stout TR. Disc Plate Method Of Microbiological Antibiotic Assay: I. Factors Influencing Variability And Error. Applied microbiology. 1971;22(4):659–665. doi.org/10.1128/am.22.4.659-665.1971

12. Woolfrey BF, Ramadei WA, Quall C. Petri Dish Concavity—A Potential Source Of Error In Antibiotic Assay And Agar Diffusion Antibiotic Susceptibility Tests. American Journal of Clinical Pathology. 1979;71(4):433–436. doi.org/10.1093/ajcp/71.4.433

13. Coyle MB. Manual of antimicrobial susceptibility testing. BCIT Imaging Services; 2005.

14. Abrahams RD. The Neighborhood Law Office Experiment. U. Chi. L. Rev. 1941;9:406.

15. Soad Tabaqchali and ZHA-R. Clinical Experience With Cefoxitin. Research and clinical forums. 1979;1(3):93–95.

16. Grove DC, Randall WA. Assay Methods Of Antibiotics. 1955.

17. Zuhair Hashim. Development And Application Of Fluorimetric Assay Methods For Some Cephalosporins And A Cephamycin In Human Biological Fluids. 1981. doi.org/10.1128/AAC.20.1.25

18. Finn RK. Theory Of Agar Diffusion Methods For Bioassay. Analytical Chemistry. 1959;31(6):975–977. doi.org/10.1021/ac60150a040

19. Hoffman EJ, Loessi JC, Moore RC. Constructions For The Solution Of The M Queens Problem. Mathematics Magazine. 1969;42(2):66–72. doi.org/10.1080/0025570X.1969.11975924

20. McGuire JM, Davis WW, Parke T V, Daily WA. A New Linear Diffusion Method For The Microbiological Assay Of Streptomycin And Dihydrostreptomycin. The Journal of clinical investigation. 1949;28(5):840–842. doi.org/10.1172/JCI102163

21. Bennett J V, Brodie JL, Benner EJ, Kirby WMM. Simplified, Accurate Method For Antibiotic Assay Of Clinical Specimens. Applied microbiology. 1966;14(2):170–177. doi.org/10.1128/am.14.2.170-177.1966

22. Singariya P, Mourya KK, Kumar P. Antimicrobial Activity Of The Crude Extracts Of Withania Somnifera And Cenchrus Setigerus In-Vitro. Pharmacognosy journal. 2012;4(27):60–65. doi.org/10.5530/pj.2012.27.10

23. Maneesh K, Vijayabhaskar K, Firdouse H, Rao PS, Prajwitha M, Swetha S. Evaluation Of Antimicrobial Of P. Vesicularis, Streptococcus Faecalis, Aeromonas Hydrophilia, Salmonela Typhae, Stphylococcus Cohni, Serratia Ficaria And E. Coli. Of Crude And N-Butanol Fraction Fruit Latex Of Carica Papaya L.(Caricaceae). Asian Journal of Pharmaceutical Research. 2021;11(2):92–94. doi.org/10.52711/2231-5691.2021.00017

24. Rajan AK, Jeyamani SVP, Lavanya R, Kaviya U. Assessment Of Antibiotic Sensitivity Patterns In A Primary Care Hospital. Research Journal of Pharmacy and Technology. 2018;11(8):3411–3414. doi.org/10.5958/0974-360X.2018.00628.5

25. Shahid SM, Umar N. Spectrum Of Antimicrobial Susceptibility Of E. Coli And Staphylococcus Aureus Isolates From Clinical Samples. Research J. Pharm. and Tech. 2015;8(10):1399–1402. doi.org/10.5958/0974-360X.2015.00251.6

26. Deshmukh MM, Ambad CS, Kendre N, Kashid NG. Biochemical Screening, Antibacterial And GC-MS Analysis Of Ethanolic Extract Of Hemidesmus Indicus (L) R. Br. Root. Research Journal of Pharmacognosy and Phytochemistry. 2019;11(2):73–80. doi.org/10.5958/0975-4385.2019.00014.1

27. Rakesh Kumar A. Antimicrobial Sensitivity Pattern Of Klebsiella Pneumonia Isolated From Pus From Tertiary Care Hospital And Issues Related To The Rational Selection Of Antimicrobials. Journal of Chemical and Pharmaceutical Research. 2013;5(11):326–331. doi.org/10.36347/sjams.2013.v01i06.0062

28. Katariya C, Arjunkumar R. Antimicrobial Effect Of Curry Leaves On Staphylococcus Aureus – An In Vitro Study . Research Journal of Pharmacy and Technology. 2019;12(7):3318. doi.org/10.5958/0974-360x.2019.00559.6

29. Kreger BE, Craven DE, McCabe WR. Gram-Negative Bacteremia: IV. Re-Evaluation Of Clinical Features And Treatment In 612 Patients. The American journal of medicine. 1980;68(3):344–355. doi.org/10.1016/0002-9343(80)90102-3

30. Kumar A, Guleria R, Bhardwaj A. Antibacterial Activity Of Methanolic And Ethanolic Extracts Of Leaves And Fruits Of Ficus Palmata Forssk. Research Journal of Pharmacognosy and Phytochemistry. 2012;4(6):310. https://rjpponline.org/AbstractView.aspx?PID=2012-4-6-5

31. Sundar S, Padmalatha K, Helasri G, Vasanthi M, Narmada BS, Lekhya B, Jyothi RN, Sravani T. Anti-microbial Activity of Aqueous Extract of Natural Preservatives-Cumin, Cinnamon, Coriander and Mint. Research Journal of Pharmacy and Technology; 2016. doi.org/10.5958/0974-360X.2016.00159.1

32. Fguira LF-B, Fotso S, Ameur-Mehdi R Ben, Mellouli L, Laatsch H. Purification And Structure Elucidation Of Antifungal And Antibacterial Activities Of Newly Isolated Streptomyces Sp. Strain US80. Research in Microbiology. 2005;156(3):341–347. doi.org/10.1016/j.resmic.2004.10.006

33. Konaté K, Mavoungou JF, Lepengué AN, Aworet-Samseny RRR, Hilou A, Souza A, Dicko MH, M’Batchi B. Antibacterial Activity Against β-Lactamase Producing Methicillin And Ampicillin-Resistants Staphylococcus Aureus: Fractional Inhibitory Concentration Index (FICI) Determination. Annals of clinical microbiology and antimicrobials. 2012;11(1):1–12. doi.org/10.1186/1476-0711-11-18

34. De Billerbeck V-G. Huiles Essentielles Et Bactéries Résistantes Aux Antibiotiques. Phytothérapie. 2007;5(5):249–253. https://link.springer.com/article/10.1007/s10298-007-0265-z

35. Franco e Franco TCC, Amoroso P, Marin JM, de Ávila FA. Detection Of Streptococcus Mutans And Streptococcus Sobrinus In Dental Plaque Samples From Brazilian Preschool Children By Polymerase Chain Reaction. Brazilian Dental Journal. 2007;18(4):329–333. doi.org/10.1590/S0103-64402007000400011

36. Das K, Tiwari RKS, Shrivastava DK. Techniques For Evaluation Of Medicinal Plant Products As Antimicrobial Agents: Current Methods And Future Trends. Journal of medicinal plants research. 2010;4(2):104–111. doi.org/10.5897/JMPR09.030

37. Abraham EP, Chain E, Fletcher CM, Gardner AD, Heatley NG, Jennings MA, Florey HW. Further Observations On Penicillin. The Lancet. 1941;238(6155):177–189. doi.org/10.1016/S0140-6736(00)72122-2

38. Vincent JG, Vincent HW, Morton J. Filter Paper Disc Modification Of The Oxford Cup Penicillin Determination. Proceedings of the society for Experimental Biology and Medicine. 1944;55(3):162–164. doi.org/10.3181/00379727-55-14502

39. Baur AW, Kirby WMM, Sherris JC, Turch M. Antibiotic Susceptibility Testing By A Standardized Single Disk Method. Am J clin pathol. 1966;45(4):493–496. doi.org/10.1128/am.13.2.279-280.1965.

40. Baker CN, Stocker SA, Culver DH, Thornsberry C. Comparison Of The E Test To Agar Dilution, Broth Microdilution, And Agar Diffusion Susceptibility Testing Techniques By Using A Special Challenge Set Of Bacteria. Journal of clinical microbiology. 1991;29(3):533–538. doi.org/10.1128/jcm.29.3.533-538.1991

41. Cooper KE, Woodman D. The Diffusion Of Antiseptics Through Agar Gels, With Special Reference To The Agar Cup Assay Method Of Estimating The Activity Of Penicillin. Journal of Pathology and Bacteriology. 1946;58(1):75–84. doi.org/10.1002/path.1700580110

42. McGuire JM, Davis WW, Parke T V, Daily WA. A New Linear Diffusion Method For The Microbiological Assay Of Streptomycin And Dihydrostreptomycin. The Journal of clinical investigation. 1949;28(5):840–842. doi.org/10.1172/JCI102163

43. Flanagan JN, Steck TR. The Relationship Between Agar Thickness And Antimicrobial Susceptibility Testing. Indian journal of microbiology. 2017;57(4):503–506. doi.org/10.1007/s12088-017-0683-z

44. Bonev B, Hooper J, Parisot J. Principles Of Assessing Bacterial Susceptibility To Antibiotics Using The Agar Diffusion Method. Journal of antimicrobial chemotherapy. 2008;61(6):1295–1301. doi.org/10.1093/jac/dkn090

45. Eversole WG, Doughty EW. The Diffusion Coefficients Of Molecules And Ions From Measurements Of Undisturbed Diffusion In A Stationary Medium. The Journal of Physical Chemistry. 2002;39(2):289–292. doi.org/10.1021/j150362a014

46. Becker EL, Munoz J, Lapresle C, Le Beau LJ. Antigen—Antibody Reactions In Agar: II. Elementary Theory And Determination Of Diffusion Coefficients Of Antigen. The Journal of Immunology. 1951;67(6):501–511. https://www.jimmunol.org/content/67/6/501

47. Humphrey JH, Lightbown JW. A General Theory For Plate Assay Of Antibiotics With Some Practical Applications. Microbiology. 1952;7(1–2):129–143. doi.org/10.1099/00221287-7-1-2-129

48. Housewright RD, Henry RJ, Berkman S. A Microbiological Method For The Assay Of Subtilin. Journal of Bacteriology. 1948;55(4):545–550. doi.org/10.1128/jb.55.4.545-550.1948

49. Rajeswari A, Ramesh S. Investigations On Pharmacological Constituent And Antimicrobial Efficacy Of Plant Diffusate Against Clinical Pathogens. Research Journal of Pharmacy and Technology. 2012;5(12):VI. https://rjptonline.org/AbstractView.aspx?PID=2012-5-12-21

50. Parisot J, Carey S, Breukink E, Chan WC, Narbad A, Bonev B. Molecular Mechanism Of Target Recognition By Subtilin, A Class I Lanthionine Antibiotic. Antimicrobial Agents and Chemotherapy. 2008;52(2):612–618. doi.org/10.1128/AAC.00836-07

51. Wu X, Guan Y, Wei G, Wang HY. Theoretical Equations For Agar-Diffusion Bioassay. Industrial and engineering chemistry research. 1990;29(8):1731–1734. doi.org/10.1021/ie00104a025

52. Kanoh S, Rubin BK. Mechanisms Of Action And Clinical Application Of Macrolides As Immunomodulatory Medications. Clinical microbiology reviews. 2010;23(3):590–615. doi.org/10.1128/CMR.00078-09

53. Tenson T, Lovmar M, Ehrenberg M. The Mechanism Of Action Of Macrolides, Lincosamides And Streptogramin B Reveals The Nascent Peptide Exit Path In The Ribosome. Journal of molecular biology. 2003;330(5):1005–1014. doi.org/10.1016/s0022-2836(03)00662-4

54. Liang J-H, Han X. Structure-Activity Relationships And Mechanism Of Action Of Macrolides Derived From Erythromycin As Antibacterial Agents. Current Topics in Medicinal Chemistry. 2013;13(24):3131–3164. doi.org/10.2174/15680266113136660223

55. Beganovic M, Luther MK, Rice LB, Arias CA, Rybak MJ, LaPlante KL. A Review Of Combination Antimicrobial Therapy For Enterococcus Faecalis Bloodstream Infections And Infective Endocarditis. Clinical Infectious Diseases. 2018;67(2):303–309. doi.org/10.1093/cid/ciy064

56. Sivapalasingam S, Steigbigel NH. Macrolides, Clindamycin, And Ketolides. Mandell, Douglas, And Bennett’s Principles And Practice Of Infectious Diseases. 2015:358–376.

57. Campoli-Richards DM, Monk JP, Price A, Benfield P, Todd PA, Ward A. Ciprofloxacin. Drugs. 1988;35(4):373–447.

58. Ball AP, Gray JA, Murdoch J. Antibacterial Drugs Today: II. Drugs. 1975;10(2):81–111.

59. Vianna JF, Bezerra KS, Oliveira JIN, Albuquerque EL, Fulco UL. Binding Energies Of The Drugs Capreomycin And Streptomycin In Complex With Tuberculosis Bacterial Ribosome Subunits. Physical Chemistry Chemical Physics. 2019;21(35):19192–19200. https://pubs.rsc.org/en/content/articlelanding/2019/cp/c9cp03631h

60. Germovsek E, Barker CI, Sharland M. What Do I Need To Know About Aminoglycoside Antibiotics? Archives of Disease in Childhood-Education and Practice. 2017;102(2):89–93.

Received on 20.06.2022 Modified on 28.07.2022

Research J. Pharm. and Tech 2023; 16(1):294-300.

DOI: 10.52711/0974-360X.2023.00053