Rapid, point-of-care (PoC) diagnostics for antibiotic susceptibility testing (AST) are critical in combating the antimicrobial resistance epidemic. While new, alternative technologies are capable of rapidly identifying antibiotic resistance, traditional AST methods, where a patient sample is incubated with different antibiotics, remain the most reliable and practical in determining antibiotic effectiveness. Here, we demonstrate a novel sample incubation technique on a microfluidic centrifugal disc (CD) as a proof of concept automated sample processing platform for AST. By using ribosomal RNA (rRNA) as a marker for cell growth, we demonstrated that incubation on the microfluidic CD was enhanced (>1.6 fold) for 11 out of 14 clinically relevant isolates of Escherichia coli compared to traditional shaker incubators. Finally, we utilize the system to identify antibiotic resistance of 11 E. coli isolates incubated with 5 different antibiotics in under 2 hours.
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http://dx.doi.org/10.1039/d0lc00838a | DOI Listing |
Plant Foods Hum Nutr
December 2024
Facultad de Ingeniería Química, Universidad Autónoma de Yucatán, Periférico Norte Km. 33.5, Tablaje Catastral 13615, Col. Chuburná de Hidalgo Inn, Mérida, 97203, Yucatán, México.
The increasing concern over microbial resistance to conventional antimicrobial agents used in food preservation has led to growing interest in plant-derived antimicrobial peptides (AMPs) as alternative solutions. In this study, the antimicrobial mechanisms of chia seed-derived peptides YACLKVK, KLKKNL, KLLKKYL, and KKLLKI were investigated against Staphylococcus aureus (SA) and Escherichia coli (EC). Fluorometric assays and scanning electron microscopy (SEM) demonstrated that the peptides disrupt bacterial membranes, with propidium iodide (PI) uptake reaching 72.
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December 2024
Cancer Center, Department of Pulmonary and Critical Care Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
Hospital-acquired infection (HAI) and antimicrobial resistance (AMR) represent major challenges in healthcare system. Despite numerous studies have assessed environmental and patient samples, very few studies have explored the microbiome and resistome profiles of medical staff including nursing workers. This cross-sectional study was performed in a tertiary hospital in China and involved 25 nurses (NSs), 25 nursing workers (NWs), and 55 non-medical control (NC).
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December 2024
Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, Chile.
Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating advanced predictive models to support clinical decision-making. In this study, we explore multi-label classification as a novel approach to predict antibiotic resistance across four clinically relevant bacteria: E. coli, S.
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December 2024
Department of Hematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland.
Patients undergoing autologous stem cell transplantation (auto-SCT) face elevated risks of infections. Additionally, patients colonized in the gastrointestinal tract with antibiotic-resistant bacteria (ARB) are at higher risk of infection with ARB and other infections. Therefore, patients colonized with ARB before auto-SCT should present with an exceptionally high incidence of infections.
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December 2024
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Candida albicans is a common opportunistic pathogen, causing infections ranging from superficial to bloodstream infections. The limited antifungal options and rising drug resistance challenge clinical treatment. We screened 98 essential oils and identified 48 with antifungal activity against Candida albicans at 1% concentration, determining their minimum inhibitory concentrations (MIC).
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