AIMC Topic: Saliva

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Discrimination of Benign and Malignant Thyroid Nodules through Comparative Analyses of Human Saliva Samples via Metabolomics and Deep-Learning-Guided Label-free SERS.

ACS applied materials & interfaces
Thyroid nodules are a very common entity. The overall prevalence in the populace is estimated to be around 65-68%, among which a small portion (less than 5%) is malignant (cancerous). Therefore, it is important to discriminate benign thyroid nodules ...

Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in saliva can provide an alternative for drug analysis in forensic toxicology. Therefore, a highly sensitive, fast, reagent-free, and sustainable approach wi...

AI-driven feature selection and epigenetic pattern analysis: A screening strategy of CpGs validated by pyrosequencing for body fluid identification.

Forensic science international
Identification of body fluid stain at crime scene is one of the important tasks of forensic evidence analysis. Currently, body fluid-specific CpGs detected by DNA methylation microarray screening, have been widely studied for forensic body fluid iden...

Diagnostic potential of salivary microbiota in persistent pulmonary nodules: identifying biomarkers and functional pathways using 16S rRNA sequencing and machine learning.

Journal of translational medicine
BACKGROUND: The aim of this study was to explore the microbial variations and biomarkers in the oral environment of patients with persistent pulmonary nodules (pPNs) and to reveal the potential biological functions of the salivary microbiota in pPNs.

A multi-class support vector machine classification model based on 14 microRNAs for forensic body fluid identification.

Forensic science international. Genetics
MicroRNAs (miRNAs) are promising biomarkers for forensic body fluid identification owing to their small size, stability against degradation, and differential expression patterns. However, the expression of most body fluid-miRNAs is relative (differen...

Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis.

Journal of gastrointestinal cancer
OBJECTIVE: Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. ...

Bacterial profile-based body fluid identification using a machine learning approach.

Genes & genomics
BACKGROUND: Identifying the origins of biological traces is critical for the reconstruction of crime scenes in forensic investigations. Traditional methods for body fluid identification rely on chemical, enzymatic, immunological, and spectroscopic te...

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time.

The Analyst
With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first ...

Salivary detection of Chikungunya virus infection using a portable and sustainable biophotonic platform coupled with artificial intelligence algorithms.

Scientific reports
The current detection method for Chikungunya Virus (CHIKV) involves an invasive and costly molecular biology procedure as the gold standard diagnostic method. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustain...

Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.

International journal of molecular sciences
Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matri...