Bacterial Infection

Decoding bacterial transcriptional regulatory networks through integrated multi-omics datasets for artificial intelligence-driven design of programmable biological systems.

Advances in next-generation sequencing (NGS) have provided refined insight into bacterial transcriptional regulatory networks (TRNs) on a genome-wide scale. The integration of genomic and transcriptomic datasets has clarified the architecture of TRNs, revealing regulatory complexity that requires computational methods for interpretation. The TRNs and their regulatory elements characterized through...

Multi-omics precision diagnosis of brucellosis: Advances in biomarker discovery and clinical application.

Brucellosis, a neglected zoonosis caused by intracellular Brucella bacteria, remains a formidable global public health challenge, especially in developing regions. The notorious ability of Brucella to evade host immunity and establish chronic focal infections limits the utility of traditional diagnostic methods like bacterial culture and serology for early detection, therapeutic monitoring, and di...

Host-Linked Virome Assembly and Turnover Predict Bacterial Community Structure in Wastewater Treatment Systems.

Viruses play crucial roles in bacterial ecology and evolution through virus-host interactions; however, their distribution, assembly mechanisms, and t...

Deep neural networks in medical microbiology for bacterial colonies classification.

While automation has transformed many areas inside clinical laboratories, microbiology still relies heavily on manual tasks, particularly the culture ...

An artificial intelligence classifier as a screening tool to rule out otitis media in children.

OBJECTIVE: Acute otitis media is the most common bacterial infection among children and a significant global health burden. Despite its high incidence...

Breaking the culture habit: Complementing culture-based veterinary diagnostics with metagenomic data -A case study of feline and canine skin infections.

BACKGROUND: Skin infections have been described as the primary cause for veterinary small animal practice visits, frequently requiring topical and sys...

dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.

SUMMARY: This study presents dAMN, a genome-scale neural-mechanistic hybrid model that combines neural networks with dynamic flux balance analysis to ...

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, particul...

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...

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...