AIMC Topic: Quantum Dots

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Deep Learning-Assisted G4 Nanowire-Enhanced Carbon Dot Biosensor for Exosomal LncRNA Artificial Intelligence Diagnosis.

Analytical chemistry
Exosomal long noncoding RNAs (lncRNA) have significant potential as a biomarker for early cancer diagnosis. Accurate and sensitive detection of this abnormal expression remains challenging. Herein, we develop an innovative dual-mode photoelectrochemi...

Machine learning-assisted multicolor identification and quantification of antidepressant drugs by waste-derived fluorescent nanoprobes: Towards green AI-based electronic tongue.

Analytica chimica acta
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...

Ultrasensitive SERS-LFA for the detection of neurofilament light chain and machine learning-assisted Alzheimer's disease classification.

Nanoscale
Neurofilament light chain (NfL), a cytoskeletal protein released during neuronal injury, is a promising biomarker, with elevated levels consistently associated with disease severity and progression in multiple neurological conditions, including Alzhe...

QDs fluorescent immunosensor based on magnetic separation coupled with machine learning for aflatoxin B1 detection in vegetable oils.

Food chemistry
Aflatoxin B1 (AFB1) is a common mycotoxin frequently found in vegetable oils. It poses a severe threat to public health, therefore there is a need for rapid and sensitive detection methods. In this study, a novel competitive immunofluorescent biosens...

Carbon dots meet artificial intelligence: applications in biomedical engineering.

Journal of materials chemistry. B
Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fie...

Functional biomaterials and machine learning approaches for phenotyping heterogeneous tumor cells and extracellular vesicles.

Biomaterials science
Heterogeneity in cancer is known to be a contributor to the formation of metastatic lesions, poor prognosis, and ultimately undermines therapeutic efficacy. This same tumor heterogeneity is reflected in circulating tumor cells (CTCs) and tumor derive...

Machine learning-assisted construction of a lignin carbon dots sensor array for detecting food colorants.

Food chemistry
Food safety monitoring is crucial due to the widespread use and potential toxicity of synthetic food colorants. High-sensitivity techniques such as chromatography are routinely employed but require costly equipment and skilled operators. Here we show...

Multifunctional electronic skin integrating dual-mode optical and pressure sensors for caregiving robots.

Nanoscale horizons
Advancements in artificial intelligence have broadened the capabilities of robots, particularly in caregiving applications that are essential for aging societies facing a growing shortage of human caregivers. Humanoid caregiving robots require sophis...

Thermodynamic Microenvironment Engineering in Mesoporous Nanoreactors to Enhance Biocatalysis for AI-Empowered Ultrasensitive Pathogen Detection.

Analytical chemistry
Harmonizing enzyme-support microenvironments to govern thermodynamic interaction landscapes presents a critical yet underexplored frontier in nanobiocatalysis for pathogen detection. Herein, we architecturally engineer mesoporous resorcinol formaldeh...

A digital fluorescence immunoassay platform using a self-driven microfluidic cartridge with magnetic capture.

Biosensors & bioelectronics
Self-driven microfluidic devices have significantly advanced point-of-care testing (POCT) by enabling integration and automation of all the components required for biochemical analysis through capillary-driven fluid flow, eliminating the need for ext...