Bacterial Infection

Managing multidrug resistant Gram-negative bacteraemia in immunocompromised hosts.

PURPOSE OF REVIEW: Multidrug-resistant Gram-negative bloodstream infections (MDR-GNBSI) are increasingly frequent in immunocompromised hosts, particularly solid organ transplant (SOT) recipients and patients with haematological malignancy (HM) receiving intensive chemotherapy and/or cellular therapies. We summarize current evidence and practical approaches across empirical, quasi-targeted and targ...

BERT-T6: Toward High-Accuracy T6SS Bacterial Toxin Identification Using a Protein Language Model.

Type VI secretion system effectors (T6SEs) are key virulence factors that disrupt critical cellular components in target cells, facilitating bacterial competition or host immune evasion. Accurate identification of T6SEs is therefore crucial for understanding bacterial pathogenesis. Although several computational predictors based on traditional machine learning and deep learning have been developed...

Comprehensive cross-cohort analysis reveals global gut microbiome signatures of celiac disease.

BACKGROUND: Celiac disease affects ~1-2% of people and remains incurable, requiring lifelong dietary restriction. The gut microbiome is thought to con...

Harnessing Terminal Signal-Aware Deep Learning for Accurate Multi-Class Secreted Effector Identification.

Gram-negative bacterial secreted effectors are translocated through specialized secretion systems to manipulate host cellular processes, and their acc...

Global Trends in Postoperative Sepsis After Pancreatoduodenectomy: A Bibliometric Analysis.

INTRODUCTION: Postoperative sepsis after pancreatoduodenectomy (PSPD) remains a major determinant of morbidity and mortality. Although extensive clini...

Classification of spinal tuberculous infection, pyogenic infection and spinal metastasis from magnetic resonance imaging using machine learning.

BACKGROUND: Differentiating between spinal tuberculosis, pyogenic (bacterial) spondylitis and spinal metastasis remains a major diagnostic challenge b...

Rapid quality evaluation of Pu-erh raw tea storage years via hyperspectral imaging coupled with machine learning and microbial profiling.

This study developed a non-destructive approach for identifying storage years and quality evolution of Pu-erh raw tea by integrating sensory evaluatio...

Artificial intelligence on chest X-ray for tuberculosis screening in Tanzania: a multicentre evaluation.

Tanzania has adopted artificial intelligence (AI)-assisted chest X-ray screening for tuberculosis (TB), including the use of CAD4TB version 6, which i...

Synthetic inducible bacteria normalize the microenvironment of refractory tumors, potentiating checkpoint inhibitor responses.

Immunotherapy has transformed cancer treatment but remains ineffective in many solid tumors, largely due to the immunosuppressive tumor microenvironme...

CARS-AMP: A Simple and Efficient Deep Learning Model for Antimicrobial Peptide Prediction.

With the increase in global antibiotic resistance, there is an urgent demand for antibiotic substitutes, for which antimicrobial peptides (AMPs) have ...

T3SS effector and regulator discovery by predicting interacting partners of T3SS chaperones in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a prominent opportunistic pathogen whose virulence is closely linked to its Type III Secretion System (T3SS), a specialized ...

Evaluation of AI-enhanced FTIR spectroscopy for species and biovar typing of intracellular pathogenic Brucella spp.

BACKGROUND: Rapid and accurate identification of intracellular pathogenic Brucella species and biovars is essential for effective public health survei...

Quantitative three-dimensional imaging of Coxiella burnetii infection by focused ion beam-scanning electron microscopy.

Coxiella burnetii is a highly virulent intracellular pathogen and the causative agent of acute and chronic Q fever in humans. Central to its pathogeni...

High-fidelity machine learning models for predicting antibacterial effects of cerium oxide nanoparticles across bacterial strains.

The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced...

Role of Ambler Position 104 in Defining Substrate Specificity in the KPC Family of β-Lactamases.

Carbapenem-resistant Gram-negative bacteria pose a critical clinical challenge, largely due to the dissemination of class A Klebsiella pneumoniae carb...

OCTN1 variants shape innate immunity and predict individual response to anti-TNFα in ulcerative colitis patients: An exploratory study.

BACKGROUND: Ulcerative colitis (UC) exhibits substantial heterogeneity in inflammatory pathways and therapeutic response. The organic cation transport...

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol.

INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...

Deep Learning-Based Protein Half-Life Prediction for Identifying Rate-Limiting Enzymes in Metabolic Pathways to Alleviate Bottleneck Reactions.

In synthetic metabolic pathways, the intracellular level of enzymes is a critical determinant of pathway efficiency and, thus, short-lived enzymes cre...

Gram staining decipherment using an artificial intelligence-powered smartphone-based application.

Gram staining provides rapid microbiological information that may assist in empirical antimicrobial selection; however, the results are often interpre...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...