Antimicrobial efficacy of neem and liquorice with chlorhexidine on Streptococcus sanguis, Streptococcus mutans, Lactobacillus and Actinomyces naeslundii - An In Vitro Study
Alqahtan, S. M.
Show abstract
The study was to formulate 2% neem and 2% liquorice mouthwashes and to compare the antimicrobial efficacy of these mouthwashes with the standard 0.2% chlorhexidine mouthwash. Alcoholic solution was prepared and added to neem mixture and liquorice mixture separately and made up to a volume of 16000 ml with purified water. Nine dilutions of each drug were done with Brain heart infusion broth (BHI) for MIC. Culture suspension was added in each serially diluted tube of 200 l. The tubes were incubated for 24 hours and observed for turbidity. Minimum inhibitory concentration (MIC) of 2% neem, 2% liquorice and 0.2% chlorhexidine against Lactobacillus, Actinomyces naeslundii, Streptococcus sanguis, Streptococcus mutans is determined by serial dilution analysis. Streptococcus mutans shows sensitivity to all three mouthwashes at a concentration starting from 0.2 g/ml. Lactobacillus shows sensitivity to neem and chlorhexidine mouthwashes at a concentration starting from 1.6 g/ml, whereas liquorice is effective at a concentration starting from 3.125 g/ml. Streptococcus sanguis shows sensitivity to chlorhexidine and liquorice mouthwashes at a concentration starting from 25 g/ml, whereas it shows sensitivity to neem at a concentration starting from 50 g/ml. Actinomyces naeslundii shows sensitivity to chlorhexidine and neem mouthwashes at a concentration starting from 1.6 g/ml, whereas it shows sensitivity to liquorice at a concentration starting from 3.125g/ml. Analysis showed an inhibition of all the four strains by the mouthwashes. The MIC for the studied mouthwashes was found to be similar to that of 0.2% chlorhexidine.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Highly Efficient Antibiofilm and Antifungal Activity of Green Propolis against Candida species in dentistry material 98%
- Antioxidant enriched fraction from Pueraria tuberosa alleviates ovariectomized-induced osteoporosis in rats, and inhibits growth of breast and ovarian cancer cell lines in vitro 95%
- Burnout: A Predictor Of Oral Health Impact Profile Among Nigerian Early Career Doctors 95%
Similar papers in this journal
- Evaluation of RNA extraction free method for detection of SARS-COV-2 in salivary samples for mass screening for COVID-19 95%
- Magnesium Sulfate Attenuates Lethality and Oxidative Damage Induced by Different Models of Hypoxia in Mice 93%
- Proteochemometric method for pIC50 prediction of Flaviviridae 92%
Similar papers in this journal
- In vitro screening of anti-viral and virucidal effects against SARS-CoV-2 by Hypericum perforatum and Echinacea. 94%
- Detailed Analysis of Surface Infection Barrier on Hands: Relationship with Morbidity to Infection Diseases and Identification of Antimicrobial Components 93%
- Electrospun cellulose acetate/gelatin nanofibrous wound dressing containing berberine for diabetic foot ulcer healing: in vitro and in vivo studies 93%
Similar papers in this journal
- Analysis of serum trace elements, macro-minerals, antioxidants, malondialdehyde and immunoglobulins in seborrheic dermatitis patients: A case-control investigation 95%
- A small H2O-soluble ingredient of royal jelly lower cholesterol levels in liver cells by suppressing squalene epoxidase 94%
- Osteoconductive material of a newly developed resin modified glass ionomer cement containing bioactive glasses for biomedical purposes 93%
Similar papers in this journal
- Atopic Biomarker Changes after Exposure to Porphyromonas gingivalis Lipopolysaccharide: A Small Experimental Study in Wistar Rat 95%
- Bacterial and Fungal Co-Infections among ICU COVID-19 Hospitalized Patients in a Palestinian Hospital: Incidence and Antimicrobial Stewardship 93%
- Analyses of spike protein from first deposited sequences of SARS-CoV2 from West Bengal, India 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.