# The Loop-Mediated Isothermal Amplification for the Rapid Detection of Porphromonas Gingivalis
## 4 Discussion  
The primary aim of this study was to demonstrate the usefulness of the LAMP method in detecting periopathogens responsible for acute and chronic periodontitis and the potential possibility of using it for fast diagnostics in an outpatient basis. We decided to undertake our studies after learning about data that suggested LAMP is a method comparable to qPCR, and some of its variants are even much faster. It was noted that LAMP is specifically useful in dental practice, as naked-eye inspection allows for an extremely fast result without expensive equipment needed for PCR and qPCR, while maintaining high sensitivity and specificity [15; 16; 21; 22; 23; 24]. After conducting the molecular analysis, the DNA of three pathogens was discovered: _Porphyomonas gingivalis_, _Fusobacterium nucleatum_, and _Tamurella forysthia_. The samples were taken from gingival fluid of patients who suffered from periodontitis. The results obtained by using the LAMP method were verified by using PCR and qPCR not only to compare their effectiveness but also their sensitivity and specificity. In contrast to the previous studies (e.g., by [PERSON] et al. [23] or [PERSON] et al. [25]), our study included more than one periopathogen when testing the LAMP method. In addition, we not only compared the LAMP method to conventional PCR, similar to some other authors (such as [PERSON] et al. [15]), but we also added qPCR, which allowed for a thorough evaluation of all three techniques being used for detecting three different periopathogens. The examined pathogens were potentially genetically heterogenic. LAMP and qPCR tests were using the fluorescent, non-specific intercalating dye as a detecting factor and not the hydrolytic hybridising probe with a specific target sequence. Considering this information, the structure of the primers used in our study was based on highly conservative gene sequences. Additionally, the selectivity of the primer/probe sets used in the LAMP reactions was tested in silico using the proper bioinformatic tools, such as the BLAST program. This was performed to minimise the risk of cross-reactivity of the related bacteria species. In contrast to PCR, the LAMP method does not require expensive specialised equipment, which, apart from its high cost, allows usage outside of well-controlled laboratory conditions. In addition to some difficulties of the LAMP technique itself (e.g., the risk of a false positive result associated with the affinity of the primer-primer sequence overlap), the study limitations include the sample size and selection of the participants. The study group consisted of patients routinely admitting for follow-up visits with an unbalanced gender and age structure, which could also affect the detection of selected periopathogens. As this was the first such study, the sample size calculation had not been performed. The smoking that may affect the periodontal condition was also not considered as an exclusion criterion. [PERSON] et al. compared the LAMP method with qPCR. The authors studied the presence of _A. actinomycetemcomitans_, _P. gingivalis_ and _P. intermedia_ in plaque samples. The results showed a higher or similar sensitivity of LAMP compared to qPCR [16]. The sensitivity and specificity comparison of the used methods indicated there was no significant difference in them in all of the evaluated pathogens. However, when detecting the _P. gingivalis_ bacteria, LAMP turned out to be, statistically, a better method than the classic PCR test and had a much shorter analysis time. A better detectability of the pathogen when using LAMP results from using a much more complex set of primers, which allows to obtain the reaction product even from a small template quantity [26]. The comparison of the specificity and sensitivity of LAMP and qPCR methods showed no significant differences between the results, regardless of the buffer (TE or Difast), in which the analysis material was secured. The LAMP method turned out to be better when detecting _P.