AIMC Topic: Fluorescent Dyes

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Machine learning-assisted triple-emission Ln-MOFs sensor array for detection of multiple PFCs in aqueous environments.

Biosensors & bioelectronics
Perfluorinated compounds (PFCs) are persistent environmental pollutants with potential carcinogenicity, posing a major threat to ecosystems and human health. Rapid identification of PFCs in complex environmental matrices remains challenging due to th...

Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis.

Nature communications
Activity recognition in live-cell imaging is labor-intensive and requires significant human effort. Existing automated analysis tools are largely limited in versatility. We present the Intelligent Vesicle Exocytosis Analysis (IVEA) platform, an Image...

Identification of Polymeric Nanoparticles Using Strategic Peptide Sensor Configurations and Machine Learning.

ACS sensors
Environmental pollution by miniaturized plastics such as micro- and nanoplastics continues to escalate, posing serious risks to ecosystems and human health. Therefore, there is an urgent need to detect or identify the plastics. Although the technique...

Ground-State Descriptor Enables Machine Learning-Assisted Virtual Screening of AIE-Active Mechanofluorochromic Molecules with High Contrast.

Journal of chemical information and modeling
Aggregation-induced emission mechanofluorochromic (AIE-MFC) molecules with high-contrast are in high demand for pressure-sensing devices and optoelectronic devices. However, developing AIE-MFC molecules with high-contrast beyond 100 nm still highly r...

Single-Protein Determinations by Magnetofluorescent Qubit Imaging with Artificial-Intelligence Augmentation at the Point-Of-Care.

ACS nano
Conventional point-of-care testing (POCT) has limitations in sensitivity with high risks of missed detection or false positive, which restrains its applications for routine outpatient care analysis and early clinical diagnosis. By merits of the cutti...

Single-Component Double-Emissive Ratiometric Probe: Toward Machine Learning Driven Detection and Discrimination of Neurological Biomarkers.

Analytical chemistry
This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the oxidation of BSA-protected Au nanoclusters (BSA-Au NCs) by -Bromosuccinimide (NBS) to detect catecholamine neurotransmitters and their metabolites, wh...

A fluorescence probe-smartphone-machine learning integrated platform for the visual and intelligent detection of imidacloprid in agricultural products.

Food chemistry
Imidacloprid is a pesticide commonly used in agriculture production. Portable and accurate detection of imidacloprid residues is of great significance to food safety and human health. Herein, a red-emitting rare earth complex (Eu-IMDC) probe is prepa...

Machine Learning-Assisted Multiplexed Fluorescence-Labeled miRNAs Imaging Decoding for Combined Mycotoxins Toxicity Assessment.

Analytical chemistry
Mycotoxins, particularly deoxynivalenol (DON) and zearalenone (ZEN), are common food contaminants that frequently co-occur in grains, posing significant health risks. This study proposed a multiplexed detection platform for simultaneous quantificatio...

Advancements in small molecule fluorescent probes for the detection of formaldehyde in environmental and food samples: A comprehensive review.

Food chemistry
Formaldehyde (FA), a hazardous substance with carcinogenicity and mutagenicity, necessitates sensitive and accurate detection methods for protecting public health and the environment. While numerous reviews have explored FA fluorescent probes, the cu...

Fluorescence 'turn-on' sensing of glial fibrillary acidic protein using graphene oxide-quenched copper nanoclusters.

Mikrochimica acta
This study introduces a fluorescence based sensing platform made to detect glial fibrillary acidic protein (GFAP), a critical biomarker associated with glioblastoma and other astrocytic malignancies. Leveraging the unique optical properties of copper...