Infectious Disease

Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study.

With the rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies, their applications in the medical field have expanded significantly. Particularly in vaccine innovation, AI and ML have shown considerable potential. This article employs bibliometric analysis to examine the progress of AI and ML in vaccine innovation over recent years. By conducting literature retri...

Deep learning-based detection of bacterial swarm motion using a single image.

Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, holds significant conceptual and clinical relevance. Conventionally, the detection of bacterial swarming involves inoculating samples on an agar surface and observing colony expansion, which is qualitative, time-intensive, and requires additional testin...

Machine learning-driven discovery of antimicrobial peptides targeting the GAPDH-TPI protein-protein interaction in Schistosoma mansoni for novel antischistosomal therapeutics.

Schistosomiasis, caused by Schistosoma mansoni, remains a significant public health burden, particularly in endemic regions with limited access to eff...

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic o...

Machine learning classification of quorum sensing-induced bacterial aggregation using flow rate assays on paper chips toward bacterial species identification in potable water sources.

Preventing waterborne disease caused by bacteria is especially important in low-resource settings, where skilled personnel and laboratory equipment ar...

Lyophilized nasal swabs for COVID-19 detection by ATR-FTIR spectroscopy: Machine learning-based approach.

The COVID-19 pandemic continues to pose challenges for global health. The disease burden and diagnostic pressure has forced scientists to explore alte...

Protease engineering: Approaches, tools, and emerging trends.

Engineered proteases with bespoke substrate specificities and activities can empower broad and innovative applications in biomedicine, mass spectromet...

Generative deep learning model assisted multi-objective optimization for wastewater nitrogen to protein conversion by photosynthetic bacteria.

For decades, the photosynthetic bacteria (PSB)-based nitrogen treatment and valorization from wastewater have been explored. However, balancing nitrog...

Novel natural vector with asymmetric covariance for classifying biological sequences.

The genome sequences of organisms form a large and complex landscape, presenting a significant challenge in bioinformatics: how to utilize mathematica...

Advances in sulfate-reducing bacteria-driven bioelectrolysis: mechanisms and applications in microbial electrolysis cell technology.

The discharge of sulfate-rich wastewater from chemical and pharmaceutical and food processing industries results in serious environmental problems tha...

Deep learning-driven hyperspectral imaging for real-time monitoring and growth modeling of psychrophilic spoilage bacteria in chilled beef.

Owing to the unsound cold chain system in China, chilled beef's quality would be affected by psychrophilic bacteria, resulting in quality deterioratio...

Bioactive films with essential oils and machine learning for controlling Aspergillus niger growth and fumonisin B production in vitro.

Aspergillus niger is an important species in the fungal community of many foods and is one of the most significant microorganisms used in biotechnolog...

Screening and preliminary analysis of antimicrobial peptide genes in Octopussinensis.

Antimicrobial peptides (AMPs) are small molecular peptides that widely exist in organisms to resist external microbial invasion and play a crucial rol...

Decoding virulence and resistance in Klebsiella pneumoniae: Pharmacological insights, immunological dynamics, and in silico therapeutic strategies.

Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the ...

Machine learning-based approaches for distinguishing viral and bacterial pneumonia in paediatrics: A scoping review.

BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource sett...

Harnessing the fish gut microbiome and immune system to enhance disease resistance in aquaculture.

The increasing global reliance on aquaculture is challenged by disease outbreaks, exacerbated by antibiotic resistance, and environmental stressors. T...

Identification of Fusarium sambucinum species complex by surface-enhanced Raman spectroscopy and XGBoost algorithm.

Rapid and reliable identification of Fusarium fungi is crucial, due to their role in food spoilage and potential toxicity. Traditional identification ...

Artificial intelligence in bacterial diagnostics and antimicrobial susceptibility testing: Current advances and future prospects.

Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. ...

CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RN...

Predicting Biological Activity from Biosynthetic Gene Clusters Using Neural Networks.

Microorganisms such as bacteria and fungi have been used for natural products that translate to drugs. However, assessing the bioactivity of extract f...