RESUMEN
Accurate and fast histological staining is crucial in histopathology, impacting diagnostic precision and reliability. Traditional staining methods are time-consuming and subjective, causing delays in diagnosis. Digital pathology plays a vital role in advancing and optimizing histology processes to improve efficiency and reduce turnaround times. This study introduces a novel deep learning-based framework for virtual histological staining using photon absorption remote sensing (PARS) images. By extracting features from PARS time-resolved signals using a variant of the K-means method, valuable multi-modal information is captured. The proposed multi-channel cycleGAN model expands on the traditional cycleGAN framework, allowing the inclusion of additional features. Experimental results reveal that specific combinations of features outperform the conventional channels by improving the labeling of tissue structures prior to model training. Applied to human skin and mouse brain tissue, the results underscore the significance of choosing the optimal combination of features, as it reveals a substantial visual and quantitative concurrence between the virtually stained and the gold standard chemically stained hematoxylin and eosin images, surpassing the performance of other feature combinations. Accurate virtual staining is valuable for reliable diagnostic information, aiding pathologists in disease classification, grading, and treatment planning. This study aims to advance label-free histological imaging and opens doors for intraoperative microscopy applications.
Asunto(s)
Tecnología de Sensores Remotos , Humanos , Animales , Ratones , Reproducibilidad de los Resultados , Eosina Amarillenta-(YS) , Hematoxilina , Coloración y EtiquetadoRESUMEN
High-molecular-weight polymeric nanoparticles are critical to increasing the loading efficacy and tuning the release profile of targeted molecules for medical diagnosis, imaging, and therapeutics. Although a number of microfluidic approaches have attained reproducible nanoparticle synthesis, it is still challenging to fabricate nanoparticles from high-molecular-weight polymers in a size and structure-controlled manner. In this work, an acoustofluidic platform is developed to synthesize size-tunable, high-molecular-weight (>45 kDa) poly(lactic-co-glycolic acid)-b-poly(ethylene glycol) (PLGA-PEG) nanoparticles without polymer aggregation by exploiting the characteristics of complete and ultrafast mixing. Moreover, the acoustofluidic approach achieves two features that have not been achieved by existing microfluidic approaches: (1) multi-step (≥2) sequential nanoprecipitation in a single device, and (2) synthesis of core-shell structured PLGA-PEG/lipid nanoparticles with high molecular weights. The developed platform expands microfluidic potential in nanomaterial synthesis, where high-molecular-weight polymers, multiple reagents, or sequential nanoprecipitations are needed.
Asunto(s)
Nanopartículas , Polímeros , Lípidos , Microfluídica , Tamaño de la Partícula , PolietilenglicolesRESUMEN
Separation of nano/microparticles based on surface acoustic waves (SAWs) has shown great promise for biological, chemical, and medical applications ranging from sample purification to cancer diagnosis. However, the permanent bonding of a microchannel onto relatively expensive piezoelectric substrates and excitation transducers renders the SAW separation devices non-disposable. This limitation not only requires cumbersome cleaning and increased labor and material costs, but also leads to cross-contamination, preventing their implementation in many biological, chemical, and medical applications. Here, we demonstrate a high-performance, disposable acoustofluidic platform for nano/microparticle separation. Leveraging unidirectional interdigital transducers (IDTs), a hybrid channel design with hard/soft materials, and tilted-angle standing SAWs (taSSAWs), our disposable acoustofluidic devices achieve acoustic radiation forces comparable to those generated by existing permanently bonded, non-disposable devices. Our disposable devices can separate not only microparticles but also nanoparticles. Moreover, they can differentiate bacteria from human red blood cells (RBCs) with a purity of up to 96%. Altogether, we developed a unidirectional IDT-based, disposable acoustofluidic platform for micro/nanoparticle separation that can achieve high separation efficiency, versatility, and biocompatibility.