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Optical barcodes are versatile information carriers widely applied for encryption, commercial anti-counterfeiting, and biomedical fields. Hydroxypropyl cellulose (HPC), as a natural derivative, exhibits excellent biocompatibility and can self-assemble into cholesteric liquid crystals (CLCs) with structure color. However, the high viscosity of HPC CLCs is a huge hurdle for material processing and thus limits their applications. In this study, a high-speed revolving microfluidic platform is developed for emulsifying high-viscosity methacrylate functionalized HPC (HPC-MA) solution to form droplets. HPC-MA molecules in the droplets can self-assemble into CLCs by water evaporation, and the resultant CLCs droplets can be cross-linked to form structural color barcode particles. The prepared HPC-MA CLCs barcoded particles exhibit well-defined and adjustable encoding information while maintaining excellent biocompatibility. Furthermore, the prepared barcode particles also demonstrate great potential in 3D cell culture and multiplex immunoassays. This work introduces an efficient way to continuously produce HPC-MA CLCs barcode particles with finely tunable size and uniformity. Such barcode particles are promising for widespread applications in bioanalysis and biodiagnostics.
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http://dx.doi.org/10.1002/advs.202506556 | DOI Listing |
Int J Biol Macromol
September 2025
College of Food Science and Engineering, Northwest A&F University, Yangling, 712100, PR China. Electronic address:
As the primary storage protein, highland barley gliadin (HBG) exhibits limitations in the processing of highland barley foods, primarily due to its abundant non-polar amino acids. In this study, HBG was utilized to prepare sugar-HBG complexes with pentose (xylose), hexoses (glucose and galactose), and disaccharides (lactose and maltose) in an aqueous system at a pH of 11 and a temperature of 75 °C. Subsequently, the structural and functional characteristics of these complexes were evaluated.
View Article and Find Full Text PDFPhysiol Meas
September 2025
College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China.
The aortic pressure waveform (APW) is relevant to diagnosing and treating cardiovascular diseases. While various non-invasive methods for APW estimation exist, more accurate and practical monitoring methods are required. This study introduces a hybrid model combining variational mode decomposition improved by particle swarm optimization (PSO-VMD) and gated recurrent unit (GRU) networks (PSO-VMD-GRU) to reconstruct the APW from the brachial pressure waveform (BPW).
View Article and Find Full Text PDFZ Med Phys
September 2025
Division of Medical Physics, Department of Radiation Oncology, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria; MedAustron Ion Therapy Center, Marie Curie-Straße 5, A-2700 Wiener Neustadt, Austria.
Context: Pre-clinical animal studies are pivotal for understanding the radiation effects in particle therapy. However, small animal research often relies on highly customized in-house solutions. This study introduces a comprehensive, open-source data processing pipeline specifically developed for pre-clinical particle irradiation research in a multi-vendor setting.
View Article and Find Full Text PDFArtif Intell Med
November 2025
Advanced Computing and e-Science Group, Institute of Physics of Cantabria (IFCA), CSIC - UC, Santander, Spain.
Artificial intelligence in medical imaging has grown rapidly in the past decade, driven by advances in deep learning and widespread access to computing resources. Applications cover diverse imaging modalities, including those based on electromagnetic radiation (e.g.
View Article and Find Full Text PDFAnal Chem
September 2025
Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
MicroRNAs (miRNAs) packaged within extracellular vesicles (EV) exhibit remarkable stability in circulation and reflect the genetic and epigenetic characteristics of their parent cells, making them promising biomarkers for cancer diagnosis. However, the intrinsic heterogeneity of EV populations and the low abundance of miRNAs in early stage cancer pose a challenge in the sensitive detection of miRNAs in tumor-cell-derived EV (TEV). Herein, we present a one-pot strategy named miR-nSTEV for specific recognition and in situ miRNA profiling of TEV at the single-particle level for precise prostate cancer (PCa) diagnosis.
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