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Isolation and characterization of the lytic bacteriophages and their application in combination with amoxicillin against Aeromonas dhakensis
Isolation and characterization of the lytic bacteriophages and their application in combination with amoxicillin against Aeromonas dhakensis
Author
Sawaengwong T., Sunthornthummas S., Wongyoo R., Surachat K., Rangsiruji A., Atithep T., Sarawaneeyaruk S., Doi K., Nantavisai K., Insian K., Pomwised R., Pringsulaka O.
Affiliations
Physics Department, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand; Department of Physics, Faculty of Science, Srinakharinwirot University, Bangkok, Thailand; National Electronics and Computer Technology Center (NECTEC), National Science and Technology Development Agency, PathumThani, Thailand
Type
Article
Source Title
Current Applied Science and Technology
ISSN
25869396
Year
2024
Volume
24
Issue
4
Open Access
All Open Access, Hybrid Gold
Publisher
King Mongkut's Institute of Technology Ladkrabang
DOI
10.55003/cast.2024.259042
Abstract
This work involved comparing Raman signals obtained from two different Raman spectroscopy configurations, using two distinct noise reduction methods. The excitation light source was a laser diode with a wavelength of 532 nm. A long-pass filter and focusing lens were utilized to block the excited light from the source and concentrate the Raman signals due to their weaker nature compared to the excited light signals. Light of 532 nm wavelength was blocked during green laser diode illumination using a long-pass filter. Two configurations were studied: transmission Raman spectroscopy (TRS) and reflection Raman spectroscopy (RRS). Raman signals from both configurations were compared, and the boxcar averaging and Vancouver Raman algorithm (VRA) noise reduction methods were investigated and compared. The results showed that Raman signals from the transmission configuration were higher than those from the reflection configuration, and noise signals were effectively reduced using both the boxcar averaging and VRA methods. ? 2024, King Mongkuts Institute of Technology Ladkrabang. All rights reserved.