Infectious Disease

Advances and challenges in the application of metagenomic sequencing for the diagnosis and treatment of infectious diseases: from pathogen spectrum identification to personalized antimicrobial strategies.

Infectious diseases remain a major global public health concern, demanding rapid and accurate identification of pathogens. Although conventional diagnostic methods such as culture, PCR, and immunological assays are widely used, they are limited by long processing times, narrow detection scopes, and poor capability for identifying unknown pathogens. untargeted shotgun metagenomic sequencing (mNGS),...

Green in-situ photoreduction synthesis of SERS substrates based on violet phosphorus arrays/silver nanoparticles for ultrasensitive detection and accurate identification of UTI bacteria.

Surface-enhanced Raman spectroscopy (SERS) holds significant promise for identifying urinary tract infection (UTI) pathogens due to its exceptional sensitivity and fingerprinting ability. However, traditional SERS substrates suffer from poor stability, high synthesis cost, and reliance on toxic reagents, which limit their applications in detecting low bacterial concentrations and multiple pathogen...

Cross-modal attention deep learning reveals how transformation products inherit life-cycle risks from parent antibiotics: Insights for environmental, ecological, health, and AMR risks.

The environmental, ecological, antimicrobial resistance (AMR), and human health risks of antibiotic transformation products (TPs) in aquatic environme...

Predicting the active sites of quinolone antibiotics interacting with organisms by deep learning and molecular docking.

Quinolones (QNs) antibiotics have become one of the most commonly used antibacterial drugs for human and animals in the world. In this study, we focus...

Aflatoxin detection in pistachio nuts: conventional methods, emerging technologies, and critical insights.

Aflatoxin contamination in pistachios, caused by Aspergillus flavus and Aspergillus parasiticus, poses significant risks to food safety and global tra...

Prediction of SARS-CoV-2 transmission dynamics based on population-level cycle threshold values: An epidemic transmission and machine learning modeling study.

Polymerase chain reaction (PCR) cycle threshold (Ct) values can be used to estimate the viral burden of Severe Acute Respiratory Syndrome Coronavirus ...

Sepsis Diagnostics via Biosensors: Engineering Platforms, Artificial Intelligence Integration, and Clinical Translation.

Sepsis remains one of the most diagnostically challenging syndromes due to its clinical heterogeneity, overlapping host-pathogen responses, and lack o...

Fuzzy logic in respiratory medicine: a systematic review of predictive and diagnostic applications.

BACKGROUND: There is increasing interest in the use of artificial intelligence (AI) to assist with respiratory diagnosis and risk prediction. Fuzzy lo...

Discovery of a novel compound against BmNPV using virtual screening based on the protein structure of the viral whole genome.

Currently, effective antiviral drugs against Bombyx mori nucleopolyhedrovirus (BmNPV) are still lacking, which has caused significant economic damage ...

Kaposi's sarcoma in individuals living with HIV: comparative assessment of AI-based clinical responses using a standardized questionnaire set.

OBJECTIVE: To comparatively evaluate the clinical responses of three digital platforms (ChatGPT 5.2, DeepSeek, Consensus) in terms of responsiveness, ...

Artificial intelligence-based prediction of postoperative sepsis in patients undergoing suction mini-percutaneous nephrolithotomy in real world practice: a multicenter analysis from the global Suction Lechnology Utility in Mini-PCNL Study (STUMPS) registry.

Discrimination between Mycobacterium tuberculosis and Mycobacterium bovis using Fourier transform infrared spectroscopy.

Zoonotic tuberculosis (TB) caused by Mycobacterium bovis (Mbo) is a neglected disease that hinders efforts to eradicate human tuberculosis. Developing...

Artificial intelligence in combating challenges in antimicrobial resistance: a narrative review.

Antimicrobial resistance (AMR) is a major global health challenge that threatens the effective prevention and treatment of infections. It arises from ...

Personalized sepsis mortality prediction: An interpretable machine learning nomogram.

PURPOSE: Sepsis remains a major cause of mortality in ICU patients, requiring accurate prognostic tools for optimal management. This study aimed to de...

Advancing DIA-Based Limited Proteolysis Workflows: Introducing DIA-LiPA.

Limited proteolysis coupled to mass spectrometry (LiP-MS) probes protein conformational dynamics, but interpretation of LiP-MS data is complicated by ...

A Machine Learning-Based Prognostic Model for Sepsis-Associated Liver Injury Using Routine Indicators.

OBJECTIVE: Sepsis-associated liver injury (SALI) occurs in approximately 40% of sepsis cases and is linked to high mortality, a challenge that may ste...

Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers.

Post-COVID-19 condition (PCC) manifests with prolonged, heterogeneous symptoms challenging both, diagnosis and therapeutic management. This three-year...

A hierarchical interaction message net for accurate molecular property prediction.

Discovering molecules with desirable molecular properties, including ADMET profiles, is of great importance in drug discovery. Existing approaches typ...

In Silico Approaches in Benzimidazole Derivatives Research: Recent Insights.

Benzimidazole remains a privileged heteroaromatic scaffold with broad therapeutic potential, spanning antimicrobial, anticancer, antitubercular, and a...

Klebsiella oxytoca: an opportunistic bacterial pathogen that poses challenges for treatment and vaccine development.

Klebsiella oxytoca is a clinically significant opportunistic bacterium that contributes to global morbidity and mortality. Despite its clinical releva...