Infectious Disease

Antimicrobial peptides-based strategies at the frontline in battling the escalating menace of methicillin-resistant Staphylococcus aureus biofilms.

Antimicrobial resistance (AMR), particularly in methicillin-resistant Staphylococcus aureus (MRSA), continues to threaten global health due to its multidrug resistance and strong biofilm-forming ability. Antimicrobial peptides (AMPs) have emerged as promising agents against MRSA biofilms because of their diverse origins, structural versatility, and unique modes of action. Natural AMPs derived from...

Mechanistic characterisation of AI-2/AIP-mediated quorum sensing governs casein hydrolysis and flavour-protease modulation in acidified milk co-fermented by binary lactic acid bacteria.

Interactions between lactic acid bacteria (LAB) shape the biochemical landscape of dairy fermentations, yet the molecular basis underpinning their synergistic behaviour remains obscure. This study shows that co-fermentation of yoghurt with Levilactobacillus brevis CGMCC1.5954 and Lacticaseibacillus casei CGMCC1.5956 markedly accelerates casein degradation and alters flavour-associated metabolic fl...

Developing machine learning classifiers for carbapenem resistance prediction in Klebsiella pneumoniae using Google's teachable machine.

We developed neural network models trained with images from Klebsiella pneumoniae genomes, encoded via Chaos Game Representation, to predict carbapene...

Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.

The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...

Vulnerabilities of feature clustering in EIT radiomics.

BACKGROUND: We aimed to determine whether unsupervised machine learning was able to discover latent and possibly clinically-relevant clusters, hidden ...

Smart three-in-one detection platform: Chemical sensing, image recognition, and machine learning for rapid identification of tetracycline antibiotics.

The hidden allergic reactions and cumulative toxic effects caused by antibiotic residues in aquatic products have become significant public health con...

Interpretable machine learning for predicting low-dose methylprednisolone effectiveness in long COVID.

Long COVID is a chronic, multisystem disease with limited response to conventional treatments. While low-dose methylprednisolone has shown effectivene...

Machine Learning-Based Multi-Omics Integration for Identification of Hepatocellular Carcinoma Biomarkers in an Egyptian Cohort.

Hepatocellular carcinoma (HCC) ranks among the most common causes of cancer-related deaths globally. The high incidence of HCC is largely linked to ch...

Harnessing artificial intelligence and machine learning to accelerate structure-based drug discovery for tuberculosis.

Shared inflammation in takotsubo syndrome and sepsis: Lipocalin-2 mediates neutrophil infiltration and cardiac damage.

BACKGROUND: Takotsubo syndrome (TTS) and sepsis often co-occur with poor outcomes, yet their underlying molecular mechanisms remain to be elucidated. ...

Utility of Artificial Intelligence-Driven Chatbots in Suggesting Solutions to Stapling Misadventures in Colorectal Surgery.

BackgroundColorectal surgery stapling misadventures are fairly common, potentially leading to serious complications. Although artificial intelligence ...

SERS on analyte-enriched blood for rapid, culture-free sepsis recognition and causative pathogen identification with super operational neural networks.

Sepsis remains a leading cause of morbidity and mortality, yet routine diagnostics are slow, culture-dependent, and often lack the sensitivity or spec...

Harnessing biological control and advanced technologies for sustainable wheat rust management: An integrated approach.

Wheat rusts caused by biotrophic fungi of the genus Puccinia continuously threaten global wheat production and food security. The rapid evolution of v...

Critical temperature and minimal water preservation of Litopenaeus vannamei in household refrigerators: Survival and quality responses.

Maintaining the survival and quality of Litopenaeus vannamei (L. vannamei) in household settings proves particularly challenging. This study aimed to ...

Construction and validation of a machine learning-based risk prediction model for invasive mechanical ventilation in AECOPD patients complicated with respiratory failure.

OBJECTIVE: This study aimed to create and validate a machine learning (ML) model to predict the likelihood of invasive mechanical ventilation (IMV) in...

Machine learning-assisted unveiling of aroma modulation by inorganic nitrogen during cider fermentation by Pichia kluyveri.

Non-Saccharomyces yeasts have been shown to enhance and diversify the aroma profile of cider. This study aimed to elucidate the regulatory role of ino...

Morphological regulation of filamentous fungi improves industrial production.

Filamentous fungi have emerged as ideal chassis cells for high-value products such as industrial enzymes, therapeutic proteins, and antibiotics, due t...

A New Proposed Approach to Categorize Sepsis Sub-phenotypes Based on Combined Trajectories of Perfusion Index and Central Venous Oxygen Saturation.

BACKGROUND: Circulatory disturbances in sepsis are heterogeneous but may manifest as a mismatch between peripheral perfusion and tissue oxygenation. P...

Beyond gas bubbles: AI analysis of the "bubble bed" microenvironment improves diagnosis of infected abdominal collections.

BACKGROUND: Accurate diagnosis of infected intra-abdominal fluid collections (IAFCs) is challenging, as the conventional "gas bubble sign" on computed...

Closed Loop Computer-based Artificial Intelligence Model "Maverik" to Help Diagnose and Differential Diagnoses of Childhood Onset Chronic Nonbacterial Osteomyelitis: Pilot Study.

BACKGROUND: Childhood-onset chronic nonbacterial osteomyelitis (CNO) is an inflammatory bone disease that has become better defined in the last 2 deca...