A novel ratiometric electrochemical assay for detection of formaldehyde in real food samples.

This study developed a novel ratiometric electrochemical sensor for detecting formaldehyde content in food. For the first time, we innovatively utilized 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole (AHMT), a traditional colorimetric probe that specifically reacts with formaldehyde, as an electrochemical probe to construct the electrochemical assay. The reaction product of AHMT with formaldehyde exhibits different redox potentials from AHMT, thereby enabling ratiometric detection of formaldehyde.

Recent Advances in Electrochemical Sensors for Formaldehyde.

Formaldehyde, a ubiquitous indoor air pollutant, plays a significant role in various biological processes, posing both environmental and health challenges. This comprehensive review delves into the latest advancements in electrochemical methods for detecting formaldehyde, a compound of growing concern due to its widespread use and potential health hazards. This review underscores the inherent advantages of electrochemical techniques, such as high sensitivity, selectivity, and capability for real-time analysis, making them highly effective for formaldehyde monitoring.

A responsive organic probe based photoelectrochemical sensor for hydrazine detection.

This study developed a new photoelectrochemical (PEC) sensor for the detection of the hydrazine (NH, HZ) based on a donor-π-bridge-acceptor (D-π-A) configuration organic photoactive dye (Dye-HZ). The dye was covalently immobilized on an FTO/TiO (FTO: fluorine-doped tin oxide) substrate, resulting in a photoanode FTO/TiO/Dye-HZ that exhibits a specific PEC response to NH. Hydrazine reacts with the acetyl group in the Dye-HZ molecule, leading to its removal and the formation of a hydroxy group.

Systemic tracking of diagnostic function modules for post-menopausal osteoporosis in a differential co-expression network view.

Post-menopausal osteoporosis is one of the most common bone diseases in women. The aim of the present study was to predict the diagnostic function modules from a differential co-expression gene network in order to enhance the current understanding of the biological processes and to promote the early prevention and intervention of post-menopausal osteoporosis. The diagnostic function modules were extracted from a differential co-expression network by the established protein-protein interaction (PPI) network analysis.