Magnetic particles for multidimensional in vitro bioanalysis

Phosphorescence approach based on silica protected carbon dots for autofluorescence interference-free and highly selective detection of fluoride

BACKGROUND

Fluoride (F-), an anion with the smallest ionic radius and highest charge density, plays an important role in biomedical and environmental processes, making the development of accurate F- detection methods of great importance. Fluorometric methods with simplicity and sensitivity have gained considerable attention in F- detection. However, their accuracy faces challenges due to issues like autofluorescence interference during real-time light excitation and limited selectivity. Therefore, it is important to establish a simple, real-time light excitation-free, and highly selective method for the accurate determination of F- in complicated samples.

RESULTS

Herein, a novel phosphorescent approach is developed for the selective and accurate detection of F- in complex samples. Phosphorescence emission CDs@SiO2 is fabricated by confining CDs in a silica protective layer. This design retains the favorable water solubility of silica while benefitting from its inertness, making it resistant to most substances. Furthermore, phosphorescent analysis without real-time light excitation eliminates autofluorescence interference, significantly improving the signal-to-noise ratio (SNR) and simplifying sample pretreatment. The specific interaction between F- and the Si-O bond can lead to the degradation of the silica protective layer, exposing the CDs to the solution, resulting in phosphorescence quenching, achieving the highly accurate and sensitive detection of F- with a linear range of 0.001-4 mM and a limit of detection (LOD) of 1 μM.

SIGNIFICANCE

This novel F- phosphorescence method based on the metal-free phosphorescent nanomaterial CDs@SiO2 integrates the benefits of no autofluorescence interference, high selectivity, and full aqueous compatibility, and its combination with a smartphone provides a simple, portable, and cost-effective detection platform for accurate and highly sensitive determination of F- in complex samples.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

A Micropillar Array Based Microfluidic Device for Rare Cell Detection and Single-Cell Proteomics

Advancements in single-cell-related technologies have opened new possibilities for analyzing rare cells, such as circulating tumor cells (CTCs) and rare immune cells. Among these techniques, single-cell proteomics, particularly single-cell mass spectrometric analysis (scMS), has gained significant attention due to its ability to directly measure transcripts without the need for specific reagents. However, the success of single-cell proteomics relies heavily on efficient sample preparation, as protein loss in low-concentration samples can profoundly impact the analysis. To address this challenge, an effective handling system for rare cells is essential for single-cell proteomic analysis. Herein, we propose a microfluidics-based method that offers highly efficient isolation, detection, and collection of rare cells (e.g., CTCs). The detailed fabrication process of the micropillar array-based microfluidic device is presented, along with its application for CTC isolation, identification, and collection for subsequent proteomic analysis.

Assessing Tumorigenicity in Stem Cell-Derived Therapeutic Products: A Critical Step in Safeguarding Regenerative Medicine

Stem cells hold promise in regenerative medicine due to their ability to proliferate and differentiate into various cell types. However, their self-renewal and multipotency also raise concerns about their tumorigenicity during and post-therapy. Indeed, multiple studies have reported the presence of stem cell-derived tumors in animal models and clinical administrations. Therefore, the assessment of tumorigenicity is crucial in evaluating the safety of stem cell-derived therapeutic products. Ideally, the assessment needs to be performed rapidly, sensitively, cost-effectively, and scalable. This article reviews various approaches for assessing tumorigenicity, including animal models, soft agar culture, PCR, flow cytometry, and microfluidics. Each method has its advantages and limitations. The selection of the assay depends on the specific needs of the study and the stage of development of the stem cell-derived therapeutic product. Combining multiple assays may provide a more comprehensive evaluation of tumorigenicity. Future developments should focus on the optimization and standardization of microfluidics-based methods, as well as the integration of multiple assays into a single platform for efficient and comprehensive evaluation of tumorigenicity.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

Responsive Sensors of Upconversion Nanoparticles

Upconversion nanoparticles are a class of luminescent materials that convert longer-wavelength near-infrared photons into visible and ultraviolet emissions. They can respond to various external stimuli, which underpins many opportunities for developing the next generation of sensing technologies. In this perspective, the unique stimuli-responsive properties of upconverting nanoparticles are introduced, and their recent implementations in sensing are summarized. Promising material development strategies for enhancing the key sensing merits, including intrinsic sensitivity, biocompatibility and modality, are identified and discussed. The outlooks on future technological developments, novel sensing concepts, and applications of nanoscale upconversion sensors are provided.