Bacterial Infection

Machine learning analysis of magnetic covalent organic framework based heterostructures extracted intracellular metabolic fingerprint for direct hypervirulent Klebsiella pneumoniae prediction.

Hypervirulent Klebsiella pneumoniae (hvKP), known for its high virulence and epidemic potential, has emerged as a significant global public health threat. Therefore, improving the identification of hvKP and enabling earlier and faster detection in the community to support subsequent effective treatment and prevention of hvKP is an urgent issue. In this study, we introduce a new approach utilizing ...

Biofilm-mediated infections; novel therapeutic approaches and harnessing artificial intelligence for early detection and treatment of biofilm-associated infections.

A biofilm is a group of bacteria that have self-produced a matrix and are grouped together in a dense population. By resisting the host's immune system's phagocytosis process and attacking with anti-microbial chemicals such as reactive oxygen and nitrogen species, a biofilm enables pathogenic bacteria to evade elimination. One of the major problems in managing chronic injuries is treating wounds c...

ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.

Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome seq...

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images.

PURPOSE: To develop three novel Vision Transformer (ViT) frameworks for the specific diagnosis of bacterial and fungal keratitis using different types...

Ratiometric, 3D Fluorescence Spectrum with Abundant Information for Tetracyclines Discrimination via Dual Biomolecules Recognition and Deep Learning.

Tetracyclines are widely used in bacteria infection treatment, while the subtle chemical differences between tetracyclines make it a challenge to accu...

Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, in...

A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections.

BACKGROUND: In hospitalized patients, inadequate antibiotic dosage leading to bacterial resistance and increased antimicrobial use intensity due to ov...

Aggregation induced emission luminogen bacteria hybrid bionic robot for multimodal phototheranostics and immunotherapy.

Multimodal phototheranostics utilizing single molecules offer a "one-and-done" approach, presenting a convenient and effective strategy for cancer the...

AI Enhanced explainable early prediction of blood culture positivity in neutropenic patients using clinical and hematologic parameters.

Leukemia patients who receive chemotherapy experience a decline in neutrophils and an increased risk of infections. Neutropenic sepsis is a life-threa...

BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for and .

Antimicrobial peptides (AMPs) are a promising alternative for combating bacterial drug resistance. While current computer prediction models excel at b...

Exploration of Novel Antimicrobial Agents against Foodborne Pathogens via a Deep Learning Approach.

The emergence of antibiotic-resistant bacteria poses a severe threat to food safety and human health, necessitating an urgent search for novel antimic...

Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.

Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wid...

Liquid-bodied antibiofilm robot with switchable viscoelastic response for biofilm eradication on complex surface topographies.

Recalcitrant biofilm infections pose a great challenge to human health. Micro- and nanorobots have been used to eliminate biofilm infections in hard-t...

deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.

Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. They contain the 21st amino acid selenocysteine (Sec)...

Enhancing Bacterial Phenotype Classification Through the Integration of Autogating and Automated Machine Learning in Flow Cytometric Analysis.

Although flow cytometry produces reliable results, the data processing from gating to fingerprinting is prone to subjective bias. Here, we integrated ...

Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.

Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associ...

Seeking Correlation Among Porin Permeabilities and Minimum Inhibitory Concentrations Through Machine Learning: A Promising Route to the Essential Molecular Descriptors.

Developing effective antibiotics against Gram-negative bacteria remains challenging due to their protective outer membrane. With this study, we invest...

Machine Learning-Assisted Prediction and Generation of Antimicrobial Peptides.

Antimicrobial peptides (AMPs) offer a highly potent alternative solution due to their broad-spectrum activity and minimum resistance development again...

Fluorescent sensor array for rapid bacterial identification using antimicrobial peptide-functionalized gold nanoclusters and machine learning.

Bacterial infectious diseases pose significant challenges to public health, emphasizing the need for rapid and accurate diagnostic tools. Here, we int...

A dataset for machine learning-based QSAR models establishment to screen beta-lactamase inhibitors using the FARM -BIOMOL chemical library.

OBJECTIVES: Beta-lactamase is a bacterial enzyme that deactivates beta-lactam antibiotics, and it is one of the leading causes of antibiotic resistanc...