![]() ![]() A warm, moist climate and a rural agricultural environment may influence the sensitivity of healthy eyes to fungi and fungal infections. lusitaniae are known to cause most human ocular infections. However, many species that are otherwise harmless but if present in improper place can cause disorders. Although among Candidaspecies, few are harmless endosymbionts for hosts such as humans. Yeasts are the microorganisms commonly found in nature, among them Candidais famous genera containing a wide range of species and sub species. The primers were further analyzed by the AmplifX tool to determine their specificity and sensitivity against Candidaspecies.Ĭonclusions: The study resulted in the development of rapid and reproducible detection strategy of Candidaspecies on the basis of computational PCR that will be very helpful for the doctors/practitioners to prescribe targeted medicine against Candidaand related causative agents. To verify the in-silico specificity of the designed primers, the NCBI-BLAST program was employed to search the primers in short, near exact sequences. A set of unique primers were designed based on the conserved region in the given yeast species. Methodology: Ribosomal RNA (18S, 5.8S and 28S) sequences of eight Candidaspecies were retrieved from GenBank/EMBL databases. Objective: Development of rapid detection method and assay for Candidaspecies based on bioinformatics tools. Rapid diagnosis and early identification of causative agent through computational based methods with high accuracy will result in effective treatment. In the present study, rapid detection method of Candida, based on specific regions (18S, 5.8S and 28S) of ribosomal RNA (rRNA) genes of eight (8) species e.g. Candidais a genus of yeast that includes about 150 different species and is the most common cause of human ocular infections. Various bioinformatics tools have been developed for finding the specific regions within the ribosomal RNA (rRNA) gene complex. The inconsistent sample was confirmed by sequencing to be consistent with the typing results determined by our method, indicating that Multi-Vision could be a useful tool for HPV detection, especially in resource-limited regions.Background: Computational analyses have shown great potentials for providing tools for the rapid detection and identification of fungi for medical, scientific and commercial purposes. Further, 105 clinical samples were successfully analyzed using our method with a high concordance rate of 99.05% (104/105) compared to a HPV typing kit. The assay demonstrates high specificity with no cross-reaction among different subtypes under several artificial sample concentrations (from 10 0 to 10 3 copies per reaction) and enables highly sensitive detection of as low as 0.5 copies/μL. Using gold nanoparticle probes (AuNPs) as a color change indicator combined with a Hamming distance 2 coding scheme, 13 high-risk HPVs and two subtypes associated with high-incidence benign lesions were successfully typed by performing six closed-tube PCRs. Herein, we proposed a multiplex visualized closed-tube PCR (Multi-Vision) for HPV typing. However, routine assays based on real-time polymerase chain reaction (qPCR) or DNA-chip hybridization are either incapable of offering detailed subtype information or involve tedious open-tube operations with the risk of cross-contamination from PCR amplicons. Specific and economic methodologies for HPV typing are crucial in cancer diagnosis and further disease control. Cervical cancer is the fourth leading cause of death in women, especially in developing countries. ![]()
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