Infectious Disease

A rapid identification study of Atractylodis Macrocephalae Rhizoma and its hot processed products based on composite feature reconstruction combined with OOA-BP algorithm.

Atractylodis Macrocephalae Rhizoma (AMR) is classified as a medicinal and edible homologous food in China. Based on the fusion of multi-source information, this study comprehensively reveals the changing patterns of appearance, texture and composition of AMR during thermal processing. The processing treatments gradually altered the hue (H), saturation (S), and value (V) of the samples, significant...

Benchmarking foundation models and parameter-efficient fine-tuning for prognosis prediction in medical imaging.

BACKGROUND AND OBJECTIVES: Despite the significant potential of Foundation Models (FMs) in medical imaging, their application to prognosis prediction remains challenging due to data scarcity, class imbalance, and task complexity, limiting their clinical adoption. This study introduces the first structured benchmark to assess the robustness and efficiency of transfer learning strategies for FMs com...

Artificial Intelligence and Machine Learning in Health Care: Current Capabilities, Emerging Potential, and Future Directions.

This article reviews how artificial intelligence and machine learning are reshaping health care. After a historical overview and glossary, we explore ...

A pilot study: Incorporating Treponema pallidum antigens into machine learning models for accurate syphilis treatment outcome assessment.

As the reliability of nontreponemal tests for evaluating syphilis treatment efficacy is increasingly questioned, we propose an optimized approach usin...

New insights into machine learning prediction techniques for real-time sanitary risk assessment in karst drinking water sources affected by faecal contamination.

Safe drinking water supply from karst aquifers faces several challenges due to their high vulnerability to contamination, which can result in abrupt w...

Decoding the transport thresholds of emerging contaminants in watersheds using explainable machine learning.

Understanding watershed emerging contaminants (ECs) transport is vital for pollution control but challenging due to complex land-climate interactions ...

Viral traits from deep mutational scanning and socio-demographic context predict SARS-CoV-2 lineage fitness across diverse countries.

OBJECTIVES: To assess the joint effects of SARS-CoV-2 viral traits (ACE2 binding, immune escape, and cell entry) and socio-demographic context on vira...

Development and validation of an interpretable machine learning model using routine laboratory biomarkers to stratify severe pneumonia risk in young children.

INTRODUCTION: Severe pneumonia is a leading infectious cause of mortality in children under 5 years globally. Early identification of high-risk cases ...

Recent advances in the management of skin and soft tissue infections.

PURPOSE OF REVIEW: Skin and soft tissue infections (SSTIs) are one of the most frequent infections that need management either in outpatient setting o...

High-throughput sequencing reveals microbial transitions in refrigerated sturgeon meat: Implications for quality assurance.

This study investigated the microbially driven spoilage mechanism of sturgeon (Acipenser baerii) under refrigerated (4 °C) aerobic storage. High-throu...

EIOFX-DT: Leveraging graph centrality metrics for feature extraction and classification of viral genetic sequences.

Many diseases have a genetic origin, and analyzing intracellular structures through genetic data yields specific features for the diagnosis and classi...

Combatting antimicrobial-resistant Neisseria gonorrhoeae: new antibiotics and the pipeline of antigonococcal therapeutics.

PURPOSE OF REVIEW: Gonorrhea is the second most prevalent bacterial sexually transmitted infection globally. The proliferation of antimicrobial-resist...

Characteristics and genomics study of Salmonella isolates in retail chicken in Shaanxi, China: Focus on comparative genomics analysis of S. Kentucky and S. enteritidis isolates from Shaanxi with those from elsewhere in China.

Salmonella is a major foodborne pathogen, frequently linked to poultry and posing serious food safety and public health risks. To investigate its epid...

Urinary Cell-Free DNA detection platform for bacterial cystitis diagnosis via spot-based machine learning.

INTRODUCTION: Bacterial cystitis is a prevalent infectious condition that is primarily caused by uropathogenic Escherichia coli (E. coli). The rapid a...

Machine learning-augmented metaproteomics reveals metabolic adaptation of anammox bacteria under high nitrogen loading rate.

Anaerobic ammonium oxidation (anammox) is a biological process in which NH4+ serves as the electron donor and NO2- as the electron acceptor to produce...

Advances in antituberculosis drug-induced liver injury: Molecular mechanisms, genetic insights, and emerging animal-free prediction models.

Approximately 10 million tuberculosis patients worldwide require drug therapies annually. However, prolonged use of tuberculocidal drugs in combinatio...

The "A-B-C" Classification Reveals Outcome Trajectories in Patients With Hepatocellular Carcinoma Under Atezolizumab/Bevacizumab.

BACKGROUND & AIMS: We aimed to identify subgroups of patients with unresectable hepatocellular carcinoma (HCC) using a non a priori, data-driven machi...

Cinnamic acid derivatives in agrochemicals: current use and future perspective.

BACKGROUND: Cinnamic acid (CA) and its derivatives are widely used in various fields because of their robust, broad-spectrum biological activities and...

Regulatory mechanism of the oprM gene in colistin resistance of acinetobacter baumannii.

BACKGROUND: Colistin resistance in Acinetobacter baumannii (AB) is a serious clinical concern. This study aimed to identify resistance-related genes a...

Decoding Data Science Upskilling: Insights From 5 Years of Data Science Projects at the Centers for Disease Control and Prevention, 2019-2023.

CONTEXT: Public health organizations are increasingly recognizing the value and potential of data science. However, a gap remains in understanding how...