Universal precautions

A Case Study for Visual Detection of a Systemic Disease: Optimizing Identification of Phony Peach Disease Based on Statistical and Machine Learning Models.

Phony peach disease (PPD), caused by subsp. (Xfm), poses a significant threat to commercial peach orchards in Georgia. Early and accurate detection is essential for effective disease management, yet visual assessment remains the primary approach for diagnosing PPD symptoms due to the high cost and logistical challenges of qPCR-based detection of Xfm. We evaluated the accuracy of visual PPD asses...

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat.

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential vaccine target with high sequence conservation across diverse strains. However, despite the potency of NHR-targeting peptides and clinical efficacy of the NHR-targeting entry inhibitor enfuvirtide, no potently neutralizing NHR-directed monoclonal antibodies (mAbs) nor antisera have been identified ...

Genomic and machine learning approaches to predict antimicrobial resistance in .

UNLABELLED: is a multidrug-resistant pathogen, which poses a major challenge to clinical management due to its increasing resistance to common antibi...

Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are...

A Semi-supervised Ultrasound Image Segmentation Network Integrating Enhanced Mask Learning and Dynamic Temperature-controlled Self-distillation.

Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is o...

Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes.

OBJECTIVES: The early diagnosis and immunoregulatory mechanisms of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remain unclear, ...

Improving Hepatitis B outcome prediction with ensemble machine learning: A study on predictive models and interpretability.

OBJECTIVE: Hepatitis B virus (HBV) is a significant global health threat, responsible for severe liver diseases such as liver failure, cirrhosis, and ...

Targeting Mycobacterial Dormancy Survival Regulator (DosR) With Generative Artificial Intelligence and Omics Methods.

Tuberculosis, driven by Mycobacterium tuberculosis, remains a global health challenge due to the pathogen's ability to enter a dormant state, evading ...

Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.

Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-su...

Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.

Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disru...

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and pred...

Multi-omics profiling of cross-resistance between ceftazidime-avibactam and meropenem identifies common and strain-specific mechanisms in clinical isolates.

is a highly versatile and resilient pathogen that can infect different tissues and rapidly develop resistance to multiple drugs. Ceftazidime-avibacta...

Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.

Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of heal...

Weakly supervised learning through box annotations for pig instance segmentation.

Pig instance segmentation is a critical component of smart pig farming, serving as the basis for advanced applications such as health monitoring and w...

Formative evaluation of the acceptance of HIV prevention Artificial Intelligence chatbots by Black gay, bisexual, and other men who have sex with men in the Southern United States: Focus group study.

Gay, bisexual, and other men who have sex with men (MSM) account for 60% of new HIV infections among Black Americans in the Southern United States (U....

Hepatitis B In Silico Trials Capture Functional Cure, Indicate Mechanistic Pathways, and Suggest Prognostic Biomarker Signatures.

In silico trials, utilizing mathematical models calibrated with clinical data, present a transformative approach to expedite drug development. We prop...

Multi-feature balanced network for clothes-changing person re-identification.

Clothes-changing person re-identification (CC-ReID) is pivotal in long-term scenes, especially when involving significant variations in clothes. The p...

Hotspots and Trends in Research on Early Warning of Infectious Diseases: A Bibliometric Analysis Using CiteSpace.

Emerging and re-emerging infectious diseases (EIDs and Re-EIDs) cause significant economic crises and public health problems worldwide. Epidemics app...

Factors Influencing the Binding of HIV-1 Protease Inhibitors: Insights from Machine Learning Models.

HIV-1 protease inhibitors are crucial for antiviral therapies targeting acquired immunodeficiency syndrome (AIDS). Hundreds of HIV-1 protease complexe...

Epidemiological Dynamics of a Visually Apparent Disease: Camera Trapping and Machine-Learning Applied to Rumpwear in the Common Brushtail Possum.

Visually apparent diseases are valuable for investigating and monitoring the occurrence and prevalence of pathogens in wildlife populations through pa...