AIMC Topic: Saliva

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Digitally Enabled AI-Interpreted Salivary Ferning-Based Ovulation Prediction: Feasibility Study.

Journal of medical Internet research
BACKGROUND: Females with irregular or unpredictable cycles, including those with polycystic ovary syndrome (PCOS), have limited options for validated at-home ovulation prediction. The majority of over-the-counter ovulation prediction kits use urinary...

Urea-mediated growth engineering of Au@Ag core-shell nanostructures: an enzymatic detection strategy with machine learning-assisted comparative analysis.

Mikrochimica acta
A non-invasive, enzyme-based colorimetric biosensor was developed for urea detection in saliva, utilizing a growth-based method with Au@Ag core-shell nanostructures, including CTAB-coated gold nanoparticles (AuNPs) and CTAB-coated gold nanorods with ...

Identification of cariogenic bacteria by click chemistry mediated polyethylene glycolized graphyne nanozymes.

Mikrochimica acta
Dental caries, one of the most common oral diseases, is mainly induced by multiple cariogenic bacteria in the oral microenvironment, so it is important to construct a method that can identify oral multiply cariogenic bacteria. Herein, a machine learn...

Microbiome-based prediction of allogeneic hematopoietic stem cell transplantation outcome.

Genome medicine
BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for hematologic malignancies but is frequently complicated by relapse and immune-mediated complications, such as graft-versus-host disease (GVHD). Emerging ...

Ensemble learning for microbiome-based caries diagnosis: multi-group modeling and biological interpretation from salivary and plaque metagenomic data.

BMC oral health
BACKGROUND: Oral microbiota is a major etiological factor in the development of dental caries. Next-generation sequencing techniques have been widely used, generating vast amounts of data which is underexplored. The advancement of artificial intellig...

Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.

Renal failure
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...

Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants.

Scientific reports
Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Spectroscopy (FTIR) is a promising technological tool that facilitates the detection and diagnosis of ...

Visualizing fatigue mechanisms in non-communicable diseases: an integrative approach with multi-omics and machine learning.

BMC medical informatics and decision making
BACKGROUND: Fatigue is a prevalent and debilitating symptom of non-communicable diseases (NCDs); however, its biological basis are not well-defined. This exploratory study aimed to identify key biological drivers of fatigue by integrating metabolomic...

Comparison of salivary statherin and beta-defensin-2 levels, oral health behaviors, and demographic factors in children with and without early childhood caries.

BMC oral health
BACKGROUND: Early childhood caries (ECC) is a widespread pediatric dental condition that is influenced by a combination of biological, behavioral, and demographic factors. Salivary biomarkers, including beta-defensin-2 (BD-2) and statherin (STATH), o...

Assessment of the transmission of live-attenuated chikungunya virus vaccine VLA1553 by Aedes albopictus mosquitoes.

Parasites & vectors
BACKGROUND: Chikungunya virus (CHIKV) is a mosquito-transmitted, arthritogenic alphavirus that causes sporadic outbreaks of often debilitating rheumatic disease. The recently approved CHIKV vaccine, IXCHIQ, is based on a live-attenuated CHIKV strain ...