Plasmonic Graphene–Gold Nanostar Heterojunction for Red-Light Photoelectrochemical Immunosensing of C-Reactive Protein

ACS Sensors, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

The development of red-light photoelectrochemical (PEC) nanoimmunosensors offers new avenues for detecting clinically relevant biomarkers with high sensitivity and specificity. Herein, the first PEC nanoimmunosensor based on a plasmonic graphene gold nanostar (AuNS) heterojunction excited 765 nm red light is presented label-free detection C-reactive protein (CRP), key biomarker inflammation. This platform leverages unique localized surface plasmon resonance effect AuNSs in combination situ generated to enhance photoelectrical conversion efficiency under monochromatic light. wavelength minimizes photodamage interference from biological samples. By optimizing nanoarchitecture utilizing bifunctional photoactive transduction platform, linear range 25-800 pg/mL achieved, limit as low 13.3 pg/mL. low-energy activation, effective electron-hole pair separation, signal amplification allow CRP's rapid, selective, sensitive real clinical samples patients low-grade chronic demonstrated consistent analytical performance across multiple samples, showing potential accurate monitoring inflammatory disorders. work highlights nanomaterials develop robust immunosensors that provide scalable, noninvasive, automated, low-background noise highly alternative diagnostics.

Язык: Английский

LCM‐YOLO: A Small Object Detection Method for UAV Imagery Based on YOLOv5

IET Image Processing, Год журнала: 2025, Номер 19(1)

Опубликована: Янв. 1, 2025

ABSTRACT This study addresses the challenges of detecting small targets and with significant scale variations in UAV aerial images. We propose an improved YOLOv5 model, named LCM‐YOLO, to tackle these challenges. Initially, a local fusion mechanism is introduced into C3 module, forming C3‐LFM module enhance feature information acquisition during extraction. Subsequently, CCFM employed as neck structure network, leveraging its lightweight convolution cross‐scale characteristics effectively improve model's ability integrate target features at different levels, thereby enhancing adaptability detection performance for targets. Additionally, multi‐head attention integrated front end head, allowing model focus more on detailed through weight distribution. Experiments VisDrone2019 dataset show that LCM‐YOLO has excellent capabilities. Compared original mAP50 mAP50‐95 metrics are by 7.2% 5.1%, respectively, reaching 40.7% 22.5%. validates effectiveness multi‐scale complex backgrounds.

Язык: Английский

The role of emerging photoactive nanostructures in electrochemical sensor construction: Synthesis, properties, challenges, and perspectives

Journal of Industrial and Engineering Chemistry, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский