For Immediate Release: September 9, 2019
Jill Hronek, Director of Marketing Communications
Telephone: +1.630.256.7527, ext. 103
E-mail: [email protected]
New SLAS Technology Auto-Commentary Released, “Rapid Single-Cell Microbiological Analysis: Toward Precision Management of Infections and Dysbiosis”
Newswise — Oak Brook, IL – A new SLAS Technology Auto-Commentary, “Rapid Single-Cell Microbiological Analysis: Toward Precision Management of Infections and Dysbiosis” is now accessible online through October 26. In this newly published paper authors Hui Li, Ph.D., and Pak King Wong, Ph.D., (The Pennsylvania State University, PA, USA), Michael Morowitz, Ph.D., (University of Pittsburgh, PA, USA) and Neal Thomas, Ph.D., (Penn State University, PA, USA) describe their development of a novel technology approach designed to help clinicians better manage bacterial infection diagnosis and treatment, reduce the improper use of antibiotics and limit the spread of drug-resistant organisms.
As bacterial infection continues to be a leading cause of death and accounts for more than $20 billion in healthcare costs in the United States each year, drug-resistant strains are also on the rise. Plus, the demand for new antibiotics is outpacing the development of new classes of antibiotics due to the high cost and low ROI of development. To circumvent this, Li, Wong, Morowitz and Thomas developed a new approach that determines the presence and classification of bacteria by their shape and size for rapid phenotypic Antimicrobial Susceptibility Testing (AST), much faster than before.
Their refined approach could improve clinical lab workflow and patient care by allowing for a more appropriate antibiotic to be prescribed in a much shorter amount of time and allow labs to identify some of the most common deadly human pathogens. Beyond the improvements in bacterial classification and identification, this single-cell analysis system will also allow for more frequent and proactive monitoring of the human microbiome in persons without an infection.
Read more about their study in an SLAS Technology Auto-Commentary at https://journals.sagepub.com/doi/full/10.1177/2472630319858922 through October 26. For more information about SLAS and its journals, visit www.slas.org/journals.
SLAS (Society for Laboratory Automation and Screening) is an international community of 19,000 professionals and students dedicated to life sciences discovery and technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.
SLAS Technology: 2018 Impact Factor 2.156. Editor-in-Chief Edward Kai-Hua Chow, Ph.D., National University of Singapore (Singapore). SLAS Technology (Translating Life Sciences Innovation) was previously published (1996-2016) as the Journal of Laboratory Automation (JALA).
SLAS Discovery: 2018 Impact Factor 2.242. Editor-in-Chief Robert M. Campbell, Ph.D., Eli Lilly and Company, Indianapolis, IN (USA). SLAS Discovery (Advancing Life Sciences R&D) was previously published (1996-2016) as the Journal of Biomolecular Screening (JBS).