A Molecular Approach for Detecting Bacteria and Fungi in Healthcare Environment Aerosols: A Systematic Review

Abstract

Molecular methods have become integral to microbiological research for microbial identification. This literature review focuses on the application of molecular methods in examining airborne bacteria and fungi in healthcare facilities. In January 2024, a comprehensive electronic search was carried out in esteemed databases including PubMed, Web of Science, and Scopus, employing carefully selected keywords such as ((bacteria) OR (virus) OR (fungi)) AND (aerosol) AND ((hospital) OR (healthcare) OR (dental office)) AND ((molecular) OR (PCR) OR (NGS) OR (RNA) OR (DNA) OR (metagenomic) OR (microarray)), following the PRISMA protocol. The review specifically targets healthcare environments with elevated concentrations of pathogenic bacteria. A total of 487 articles were initially identified, but only 13 met the inclusion criteria and were included in the review. The study disclosed that the prevalent molecular methodology for appraising aerosol quality encompassed the utilization of the PCR method, incorporating either 16S rRNA (bacteria) or 18S rRNA (fungi) amplification techniques. Notably, five diverse molecular techniques, specifically PFGE, DGGE, SBT, LAMP, and DNA hybridization methods, were implemented in five distinct studies. These molecular tests exhibited superior capabilities compared to traditional bacterial and fungal cultures, providing precise strain identification. Additionally, the molecular methods allowed the detection of gene sequences associated with antibiotic resistance. In conclusion, molecular testing offers significant advantages over classical microbiological culture, providing more comprehensive information.

Discrepancies in Cephalometric Analysis Results between Orthodontists and Radiologists and Artificial Intelligence: A Systematic Review

“…All studies incorporated into the systematic review were required to adhere to the following criteria: they had to investigate discrepancies in cephalometric analysis results between orthodontists and radiologists, as well as between orthodontists and artificial intelligence (AI), encompassing both manual and digital methods of analysis. Additionally, studies needed to be published in English, with no restrictions on the publication date [26,[28][29][30][31][32][33][34][35][36][37][38]. The authors of this review established the following exclusion criteria: studies written in languages other than English, comparisons solely between two orthodontists, clinical reports, opinions, editorial papers, review articles, and studies lacking a full-text version [26,[28][29][30][31][32][33][34][35][36][37][38].…”

“…Additionally, studies needed to be published in English, with no restrictions on the publication date [26,[28][29][30][31][32][33][34][35][36][37][38]. The authors of this review established the following exclusion criteria: studies written in languages other than English, comparisons solely between two orthodontists, clinical reports, opinions, editorial papers, review articles, and studies lacking a full-text version [26,[28][29][30][31][32][33][34][35][36][37][38].…”

“…The risk of bias was categorized as follows: 0-2 points denoted a high risk, 3-4 points denoted a moderate risk, and 5-6 points indicated a low risk. Any discrepancies in scoring were resolved through discussion until a consensus was reached [26,[28][29][30][31][32][33][34][35][36][37][38].…”