AIMC Topic: Anti-Bacterial Agents

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Machine learning-enabled microfluidic ratiometric fluorescence sensor array based on lanthanide-gold nanoclusters for visual detection of multicomponent antibiotics.

Biosensors & bioelectronics
The accumulation of multiple antibiotics in the environment poses severe threats to ecosystems and human health, demanding rapid, sensitive, and portable detection methods. This study introduces a lanthanide-gold nanocluster (AuNCs)-based microfluidi...

The SERS method based on the COF-ag substrate, combined with machine learning, is used for the detection of tetracycline and oxytetracycline in milk.

Food chemistry
Tetracycline antibiotics, valued for potent antibacterial effects, are widely used in livestock but raise concerns over unsafe residues in milk. In this study, a surface-enhanced Raman spectroscopy (SERS) method based on an amino-functionalized coval...

Optimal antibiotic use in the intensive care unit.

Critical care (London, England)
BACKGROUND: Antibiotic resistance has emerged as one of the most important factors influencing the outcomes of patients with life-threatening infections in the ICU. The increasing prevalence of antibiotic-resistant infections globally highlights the ...

Analysis of disruptive action of electrical current on cell membrane integrity and modelling its antimicrobial activity.

Archives of microbiology
It is essential to eliminate harmful microbes from vital aspects of our lives, including dental instruments and other healthcare devices, cosmetics, foods, and products that come into contact with them. Electrical stimulation (ES) has been proposed t...

Artificial neural network optimized green synthesis of cysteine-conjugated silver nanoparticles for antibacterial activity against staphylococcus nepalensis to combat cystitis.

Antonie van Leeuwenhoek
The emergence of multidrug-resistant pathogens has increased the urgency for alternative treatment options for infections like cystitis. This study focused on the green synthesis of silver nanoparticles and cysteine-conjugated silver nanoparticles ut...

A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistant pneumonia caused by the 23S rRNA A2063G mutation.

Microbiology spectrum
This study aims to develop a machine learning (ML)-based predictive model for assessing the risk of multilobar pulmonary consolidation in children with macrolide-resistant pneumonia (MRMP) caused by the 23S rRNA A2063G mutation, a subgroup underrepr...

Unravelling mutation patterns in Extended-Spectrum β-Lactamases for precision drug design against AMR in Enterobacteriaceae.

Molecular genetics and genomics : MGG
Antimicrobial resistance (AMR) presents a critical global challenge, causing over 1.27 million deaths annually, with projections reaching 10 million by 2050. Among the most concerning contributors are Enterobacteriaceae, particularly Escherichia coli...

AI verification for spirulina's antimicrobial power in total coliform and Staphylococcus aureus isolated from tilapia fillet.

Scientific reports
Seafood products, including fresh tilapia fillets, are highly susceptible to rapid quality deterioration due to microbial contamination, posing a significant concern for food safety and public health. This study investigated, both experimentally and ...

Novel antimicrobial peptide HFIAP-1 mutant as a β-lactamase inhibitor against extended-spectrum β-lactamases of Escherichia coli: a comprehensive in-silico approach.

Archives of microbiology
Extended-spectrum β-lactamases in Escherichia coli poses a significant threat for clinicians in tertiary healthcare settings, rendering treatments ineffective with newer β-lactam-β-lactamase inhibitors combinations. To overcome this, the present stud...