亚洲知识产权资讯网为知识产权业界提供一个一站式网上交易平台,协助业界发掘知识产权贸易商机,并与环球知识产权业界建立联系。无论你是知识产权拥有者正在出售您的知识产权,或是制造商需要购买技术以提高操作效能,又或是知识产权配套服务供应商,你将会从本网站发掘到有用的知识产权贸易资讯。

Rapid Antibiotic Susceptibility Testing

详细技术说明
Antibiotic resistance has become a significant public health threat. It causes billions of healthcare-related costs as well as 2 million hospitalizations and 23,000 deaths annually in the US alone. Clinical treatment of bacterial infections, especially in acute cases of sepsis, requires multiple steps, including antibiotic susceptibility testing (AST). Current AST techniques are slow and limited to cultivable strains of bacteria, leading to delayed administration of appropriate antibiotics and often putting patients at risk. This also leads to rampant broad-spectrum antibiotic use, which contributes to the antibiotic resistance epidemic. Rapid AST technologies are needed to reduce morbidity and mortality rates and administer accurate antibiotic treatment at the earliest possible treatment stage.  Researchers at Arizona State University have developed a rapid AST based on the detection of individual bacterial cells in a clinical sample with an imaging technology. This technique detects bacterial cells without the need to culture or enrich the sample. It also includes a novel algorithm that allows automatic determination of antibiotic minimum inhibitory concentration and minimum bactericidal concentration values from the images. This algorithm can automatically differentiate antibiotic susceptible bacterial cells from antibiotic resistant cells.  This rapid test is a powerful tool for clinical diagnostics and antimicrobial drug development that enables precise antibiotic administration to help reduce morbidity and save patient lives. Potential Applications•       Clinical diagnostics•       Drug development Benefits and Advantages•       Rapid, universal detection of antibiotic resistant strains (<1hr) – works on cultivable, non-cultivable and slow growing microbial species•       Can image single bacterial cells at concentrations as low as 103 CFU/mL•       Doesn’t require culturing and sample enrichment•       Automatically determines antibiotic minimum inhibitory concentration and minimum bactericidal concentration values•       Characterizes antibiotic susceptibility on single cells in a mixed bacterial population•       Tracks the metabolically driven motion of each cell•       Can resolve bacterial cells in a complex matrix of sera, body fluid, etc. •       Improved clinical diagnoses leading to reduced healthcare costs For more information about the inventor(s) and their research, please see Dr. Tao’s departmental webpage
*Abstract
None
*Principal Investigation

Name: Nongjian (nj) Tao, Professor -FY18

Department: Fulton - ECEE, Bio - CBB -FY18


Name: Hui Yu, Assistant research scientist

Department: Bio - Center for Bioelectronics and Biosensors


Name: Shaopeng Wang, Research Professor

Department:

国家/地区
美国

欲了解更多信息,请点击 这里
移动设备