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Tundra lists 2 Antibiotic Resistance Genes clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT07887204
Antibiotic Resistance Genes in Periodontitis
Antimicrobial resistance (AMR) is a major global public health concern, and the oral microbiome may serve as an important reservoir of antibiotic resistance genes (ARGs). Periodontitis is a chronic inflammatory disease characterized by dysbiosis of the subgingival microbiome and progressive destruction of tooth-supporting tissues. The complex microbial communities within subgingival biofilms may facilitate the exchange of ARGs through horizontal gene transfer (HGT), potentially contributing to the dissemination of antimicrobial resistance. This observational study aims to comparatively investigate the microbial composition, antibiotic resistance gene profiles, and associated mobile genetic elements (MGEs) in the subgingival microbiomes of periodontally healthy individuals and patients with periodontitis using shotgun metagenomic sequencing. Subgingival plaque samples will be collected from 50 participants, including 25 periodontally healthy individuals and 25 patients diagnosed with periodontitis, attending Istanbul University Faculty of Dentistry. Following microbial DNA extraction, shotgun metagenomic sequencing will be performed to characterize the taxonomic and functional composition of the subgingival microbiome. Bioinformatic analyses will be conducted using established databases and tools, including CARD, RGI, ARGs-OAP, MobileElementFinder, PlasmidFinder, ICEberg, and ISfinder, to identify ARGs, characterize MGEs, and investigate their potential associations. The study will compare the diversity, abundance, and distribution of ARGs and MGEs between the two groups and assess the potential relationship between periodontal dysbiosis and the genetic capacity for horizontal transfer of antibiotic resistance. By providing a comprehensive characterization of the subgingival resistome and its associated mobile genetic elements, this study aims to improve understanding of the potential contribution of periodontal disease to antimicrobial resistance and provide scientific evidence supporting the rational use of antibiotics in periodontal care.
Gender: All
Ages: 18 Years - 65 Years
Updated: 2026-10-21
NCT01904188
Clinical Microbial Species & Antibiotic Resistance ID in ED Patients Presenting With Infection - is Rapid ID Possible & Accurate?
The aim of this project is to test the utility of The Gene Z device (as of 2018 Gene Z no longer being used), now using In-Dx and other rapid identification techniques that the investigators have developed in the lab on clinically obtained bodily fluid samples taken from patients with suspected infection or sepsis based on having three of four positive Systemic Inflammatory Response Syndrome markers, or having a known infection for which a specimen is being collected. Specimens will be collected at the University of Michigan Health/Sparrow and McLaren Greater Lansing , processed in our lab and stored for analysis at a later date to determine if the microbial pathogens identified by current methods of culture, as well as pathogen susceptibility to antibiotics by culture results, can be identified by the GeneZ technology (no longer in use) or other developed technology accurately, and more timely. It will not affect current patient care nor impact patient care, which will continue in the standard fashion today for sepsis. Results will be compared to standard culture results and antibiotic sensitivities. A secondary aim is related to the antibiotic resistance of the organism causing the infection in an attempt to determine if there are specific characteristics of the organism that allow it to be resistant to certain antibiotics. This requires analysis of the genetic material of the organism in our laboratory. Because there are also human cells in the specimens collected, with separate permission we will evaluate the human genome of the patient with the infection to determine characteristics and conditions that may predict a complicated versus uncomplicated disease course.
Gender: All
Ages: 18 Years - Any
Updated: 2026-06-08
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