AIMC Topic: Gram-Negative Bacteria

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Integrating AI-assisted SERS Biosensing and Photoactivated Antibacterial Therapy in Au@CuSe for Combating Multidrug-Resistant Bacteria.

Analytical chemistry
The escalating global crisis of multidrug-resistant (MDR) bacteria demands innovative strategies that bypass conventional antibiotic limitations. This study introduced a multifunctional Au@CuSe core-shell nanoplatform integrating artificial intellige...

Advancing virulence factor prediction using protein language models.

BMC biology
BACKGROUND: Bacterial infections rank as the second leading cause of death globally, with virulence factors (VFs) being crucial to their pathogenicity. Predicting VFs accurately can uncover mechanisms of bacterial diseases and suggest new treatments....

Rapid colorimetric antimicrobial susceptibilities direct from positive blood culture for Gram-negative bacteria.

Microbiology spectrum
UNLABELLED: Bloodstream infections (BSIs) have become increasingly challenging to treat due to emerging antimicrobial resistance (AMR). As rapid administration of appropriate antimicrobials is crucial to positive patient outcomes, clinical alternativ...

Measurement and prediction of small molecule retention by Gram-negative bacteria based on a large-scale LC/MS screen.

Scientific reports
The challenge of assessing intracellular accumulation represents a major hurdle to the discovery of new antibiotics with Gram-negative activity. To address this, a high-throughput assay was developed to measure compound uptake and retention in Escher...

High procalcitonin level is related to blood stream infections, gram-negative pathogens, and ICU admission in infections of adult febrile cancer patients.

Journal of the Egyptian National Cancer Institute
BACKGROUND: Blood stream infection (BSI) represent a life-threatening condition. Thus, we aimed to investigate the role of procalcitonin (PCT) and C-reactive protein (CRP) tests in adult febrile patients with BSI and other clinical infections in hosp...

Label-free rapid antimicrobial susceptibility testing with machine-learning based dynamic holographic laser speckle imaging.

Biosensors & bioelectronics
Antimicrobial resistance (AMR) presents a significant global challenge, creating an urgent need for rapid and sensitive antimicrobial susceptibility testing (AST) methods to guide timely treatment decisions. Traditional AST techniques, such as broth ...

A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

Journal of clinical microbiology
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecu...

Capabilities of GPT-4o and Gemini 1.5 Pro in Gram stain and bacterial shape identification.

Future microbiology
Assessing the visual accuracy of two large language models (LLMs) in microbial classification. GPT-4o and Gemini 1.5 Pro were evaluated in distinguishing Gram-positive from Gram-negative bacteria and classifying them as cocci or bacilli using 80 Gra...

Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning.

BMC medical informatics and decision making
BACKGROUND: Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the results from doctor's order.