Recent Progress in Saliva-Based Sensors for Continuous Monitoring of Heavy Metal Levels Linked with Diabetes and Obesity

Sensors are versatile technologies that provide rapid and efficient diagnostic results, making them invaluable tools in public health for measuring and monitoring community exposure to environmental contaminants. Heavy metals such as lead, mercury, and cadmium, commonly found in food and water, can accumulate in the body and have toxic effects, contributing to the development of conditions like obesity and diabetes. Traditional methods for detecting these metals often require invasive blood samples; however, sensors can utilize saliva, offering a noninvasive and simplified approach for public health screening. The use of saliva as a diagnostic fluid represents a major advance in population health monitoring due to its low cost, noninvasiveness, and ease of collection. Recent advances in sensor technology have enabled the development of diagnostic tests that link heavy metal levels in saliva with the risk of developing obesity and diabetes. Optimizing these sensors could facilitate the identification of individuals or groups at risk, enabling targeted, personalized preventive measures. Sensors that use saliva for detecting heavy metals hold promise for diagnosing and preventing metabolic diseases, providing valuable insights into the link between heavy metal exposure and metabolic health.

Authors

Institutions

Publication Details

Journal
Chemosensors
Published
2024-12-19
DOI
https://doi.org/10.3390/chemosensors12120269
Citations
9
Primary Topic
Electrochemical sensors and biosensors
Type
article
Field-Weighted Citation Impact
1.88
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Recent Progress in Saliva-Based Sensors for Continuous Monitoring of Heavy Metal Levels Linked with Diabetes and Obesity

Wesley K. Savage, Liliana Anchidin-Norocel, Claudiu Cobuz, Mihai Dimian et al.
9 citations
Chemosensors
Electrochemical sensors and biosensors
1.88
article

Recent Progress in Saliva-Based Sensors for Continuous Monitoring of Heavy Metal Levels Linked with Diabetes and Obesity

Wesley K. Savage, Liliana Anchidin-Norocel, Claudiu Cobuz, Mihai Dimian, Alexandru Nemțoi
article en
9 citations

Abstract

Sensors are versatile technologies that provide rapid and efficient diagnostic results, making them invaluable tools in public health for measuring and monitoring community exposure to environmental contaminants. Heavy metals such as lead, mercury, and cadmium, commonly found in food and water, can accumulate in the body and have toxic effects, contributing to the development of conditions like obesity and diabetes. Traditional methods for detecting these metals often require invasive blood samples; however, sensors can utilize saliva, offering a noninvasive and simplified approach for public health screening. The use of saliva as a diagnostic fluid represents a major advance in population health monitoring due to its low cost, noninvasiveness, and ease of collection. Recent advances in sensor technology have enabled the development of diagnostic tests that link heavy metal levels in saliva with the risk of developing obesity and diabetes. Optimizing these sensors could facilitate the identification of individuals or groups at risk, enabling targeted, personalized preventive measures. Sensors that use saliva for detecting heavy metals hold promise for diagnosing and preventing metabolic diseases, providing valuable insights into the link between heavy metal exposure and metabolic health.

ChemosensorsVol. 12(12)
Ştefan cel Mare University of Suceava (RO)
Good health and well-being
Openalex Percentile: Top 14%
Electrochemical sensors and biosensors
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.