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Drug Resistance, Multiple, Bacterial

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Antimicrobial and synergistic activity of thiazoline derivatives in combination with conventional antibiotics against multidrug resistant Staphylococcus aureus isolated from abscess drainage samples.

Pakistan journal of pharmaceutical sciences
Emergence and spread of multidrug resistant (MDR) Staphylococcus aureus strains is becoming major challenge in treatment of soft tissue infections. This study aimed to explore antimicrobial and synergistic antimicrobial potential of three commerciall...

[Antibacterial activity of silver nanoparticles against multiple drug resistant strains].

Wei sheng wu xue bao = Acta microbiologica Sinica
OBJECTIVE: The objective of the study was to assess the antimicrobial activity of silver nanoparticles (AgNPs) against multiple drug resistant strains.

Single and joint antibacterial activity of aqueous garlic extract and Manuka honey on extended-spectrum beta-lactamase-producing Escherichia coli.

Transactions of the Royal Society of Tropical Medicine and Hygiene
BACKGROUND: Multidrug resistance and recent technological advances have renewed interest in natural product drug discovery from ancient remedies such as Allium sativum (garlic) and honey. This study assessed antibacterial activity of aqueous garlic e...

Pathogen Identification Direct From Polymicrobial Specimens Using Membrane Glycolipids.

Scientific reports
With the increased prevalence of multidrug-resistant Gram-negative bacteria, the use of colistin and other last-line antimicrobials is being revisited clinically. As a result, there has been an emergence of colistin-resistant bacterial species, inclu...

Harnessing robotic automation and web-based technologies to modernize scientific outreach.

PLoS biology
Technological breakthroughs in the past two decades have ushered in a new era of biomedical research, turning it into an information-rich and technology-driven science. This scientific revolution, though evident to the research community, remains opa...

Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

BMC bioinformatics
BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine L...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

Journal of medical microbiology
, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of is increasing year by year, posing a severe threat to public health worldwide. has been listed as one of the pathogens causing the global c...

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Scientific reports
Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic s...