Infectious Disease

Synergistic flavor enhancement and polycyclic aromatic hydrocarbons inhibition in roasted fish by Perilla-clam/yeast composite extracts: Regulation of Maillard reaction and lipid oxidation pathways.

Flavor and safety are paramount for the quality of roasted fish. This study investigated the effects of perilla extract (ZS) and its composites with clam (GE) or yeast (YE) extracts on flavor and polycyclic aromatic hydrocarbons (PAHs) in roasted fish using a sensomics approach. All treatments reduced fishy odor (by 26.2%-42.1%) and enhanced desirable aromas, with the YE group achieving the highes...

Biophysical properties and phenotypes of cell clusters detached from Staphylococcus epidermidis biofilms after matrix-targeted disruption.

Bacterial cells detached from Staphylococcus epidermidis biofilms are found to release predominantly as small oblate clusters (∼1.9 µm) in both untreated biofilms and biofilms treated with matrix-targeted disruptors. Quantitative image analysis common to colloidal science was applied to quantitatively evaluate the physical properties of 9147 bacterial clusters detached from S. epidermidis biofilms...

TF-VSF: A Novel Training-Free Visual-Semantic Fusion Rare Medical Morning Glory Syndrome Diseases Severity Assessment Method.

Medical morning glory syndrome (MGS) is a rare congenital disease. Approximately 50% of MGS patients present with retinal detachment. Widespread scree...

Identification of tuberculosis transmission hotspots in urban China using surveillance data: a machine learning approach based on genomic and spatial analysis.

Machine learning-based analysis of prognostic factors in patients with tuberculous meningitis.

Operationalising One Health for epidermal parasitic skin diseases: threshold-triggered mass drug administration and a minimal indicator set.

Epidermal parasitic skin diseases (EPSDs)-including scabies, pediculosis, cutaneous leishmaniasis, tungiasis and cutaneous larva migrans-affect millio...

Risks of Microplastics Shaping Viral Communities and Functions in Real Marine Environments.

Microplastic (MP) pollution has become a global issue, especially in the oceans. However, the extent of changes in the ecological states of viruses th...

Genomic evolution of SARS-CoV-2 delta variants pre- and post-omicron emergence using alignment-free machine learning models.

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Predicting oil contamination in water using machine learning on microbial compositions.

We present a compact and generative machine-learning framework that predicts oil contamination based on microbial community compositions from experime...

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

PURPOSE: Digital cough screening for COVID-19 detection shows promise, but population differences in cough acoustics and screening accuracy require in...

Machine learning prediction of positive urine cultures in an academic pediatric emergency department (ED).

BACKGROUND: Urinary tract infections (UTIs) are among the most common pediatric infections, but urine culture, the diagnostic gold standard, requires ...

Quantile regression forest-based early warning of Salmonella foodborne risk using multi-source food safety surveillance data.

Salmonella is one of the most common foodborne pathogens worldwide, with transmission closely linked to contamination across multiple food products. E...

Mapping the evidence on environmental health services in healthcare facilities in low- and middle-income countries: A systematic literature inventory of over 4,000 studies.

BACKGROUND: Environmental health services in healthcare facilities-including water, sanitation, hygiene, waste management, cleaning, and infection con...

Applying machine learning to identify unrecognized COVID-19 deaths recorded as other causes of death in the United States.

The actual number of US deaths caused by severe acute respiratory syndrome coronavirus 2 infection has been investigated and debated since the start o...

Piperacillin/tazobactam plus erythromycin improves clinical outcomes in AECOPD with bacterial lower respiratory tract infections: a retrospective cohort study.

Integrating machine learning and artificial intelligence in the management of Acinetobacter infections: a narrative review.

Acinetobacter baumannii, particularly in its multidrug-resistant (MDR) and carbapenem-resistant (CRAB) forms, has become a major global health concern...

Focusing on Data to Improve Machine Learning-Guided Antibiotic Discovery.

Machine learning (ML) is poised to accelerate antibiotic discovery by rapidly identifying and generating compounds with desirable properties. Despite ...

Prediction-guided clustering for sepsis phenotyping: a retrospective cohort analysis.

BACKGROUND: Sepsis is a major cause of morbidity and mortality worldwide, with its heterogeneous and dynamically evolving clinical presentation compli...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically ill patients with gram-positive bacterial infection...

Interrater Reliability of Electroencephalogram Interpretations in Febrile Comatose African Children: Implications for Automated Interpretation Algorithm Creation.

Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in r...