Phenotypic and molecular characterization of Solobacterium moorei isolates from patients with wound infection
Abstract
Though seldom reported, Solobacterium moorei, which was first described in 2000, has been identified in specimens from patients with root canals, periradicular lesions, periodontal disease, dentoalveolar abscesses, bacteremia, septic thrombophlebitis, and halitosis. In the present study, we describe 9 cases of mixed wound infection, from a pool of 400 surgical wound infections that we have studied, in which S. moorei was isolated or found in a clone library. All isolates of S. moorei were identified by 16S rRNA gene sequence analysis, and then six were examined for their physiological and biochemical characteristics and for antimicrobial susceptibility. The results of the present study indicate that Solobacterium moorei may be a significant component in some mixed surgical wound infections and that surgical management and antimicrobial therapy may be indicated when these bacteria are identified in significant situations.
How strong is the evidence?
Evidence Hub reads this as a case report, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Ferulic acid regulates the AKT/GSK-3β/CRMP-2 signaling pathway in a middle cerebral artery occlusion animal model
- Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure–Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli
- Photochemical behavior of levofloxacin
- Correlation Between Dissolution Profiles of Salt-Form Drugs in Biorelevant Bicarbonate Buffer and Oral Drug Absorption: Importance of Dose/ Fluid Volume Ratio
- Evaluation of the synergistic potential and mechanisms of action for de novo designed cationic antimicrobial peptides
- Synthesis of [11C]levofloxacin
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.