Host-Guest Self-Assembled Interfacial Nanoarrays for Precise Metabolic Profiling

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Multidimensional Interactive Cascading Nanochips for Detection of Multiple Liver Diseases via Precise Metabolite Profiling

It is challenging to detect and differentiate multiple diseases with high complexity/similarity from the same organ. Metabolic analysis based on nanomatrix-assisted laser desorption/ionization mass spectrometry (NMALDI-MS) is a promising platform for disease diagnosis, while the enhanced property of its core nanomatrix materials has plenty of room for improvement. Herein, a multidimensional interactive cascade nanochip composed of iron oxide nanoparticles (FeNPs)/MXene/gold nanoparticles (AuNPs), IMG, is reported for serum metabolic profiling to achieve high-throughput detection of multiple liver diseases. MXene serves as a multi-binding site and an electron-hole source for ionization during NMALDI-MS analysis. Introduction of AuNPs with surface plasmon resonance (SPR) properties facilitates surface charge accumulation and rapid energy conversion. FeNPs are integrated into the MXene/Au nanocomposite to sharply reduce the thermal conductivity of the nanochip with negligible heat loss for strong thermally-driven desorption, and construct a multi-interaction proton transport pathway with MXene and AuNPs for strong ionization. Analysis of these enhanced serum fingerprint signals detected from the IMG nanochip through a neural network model results in differentiation of multiple liver diseases via a single pass and revelation of potential metabolic biomarkers. The promising method can rapidly and accurately screen various liver diseases, thus allowing timely treatment of liver diseases.

AuNPs/CNC Nanocomposite with A "Dual Dispersion" Effect for LDI-TOF MS Analysis of Intact Proteins in NSCLC Serum Exosomes

Detecting exosomal markers using laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS) is a novel approach for examining liquid biopsies of non-small cell lung cancer (NSCLC) samples. However, LDI-TOF MS is limited by low sensitivity and poor reproducibility when analyzing intact proteins directly. In this report, gold nanoparticles/cellulose nanocrystals (AuNPs/CNC) is introduced as the matrix for direct analysis of intact proteins in NSCLC serum exosomes. AuNPs/CNC with "dual dispersion" effects dispersed and stabilized AuNPs and improved ion inhibition effects caused by protein aggregation. These features increased the signal-to-noise ratio of [M+H]+ peaks by two orders of magnitude and lowered the detection limit of intact proteins to 0.01 mg mL-1. The coefficient of variation with or without AuNPs/CNC is measured as 10.2% and 32.5%, respectively. The excellent reproducibility yielded a linear relationship (y = 15.41x - 7.983, R2 = 0.989) over the protein concentration range of 0.01 to 20 mg mL-1. Finally, AuNPs/CNC-assisted LDI-TOF MS provides clinically relevant fingerprint information of exosomal proteins in NSCLC serum, and characteristic proteins S100 calcium-binding protein A10, Urokinase plasminogen activator surface receptor, Plasma protease C1 inhibitor, Tyrosine-protein kinase Fgr and Mannose-binding lectin associated serine protease 2 represented excellent predictive biomarkers of NSCLC risk.

Self-Assembled Hyperbranched Gold Nanoarrays Decode Serum United Urine Metabolic Fingerprints for Kidney Tumor Diagnosis

Serum united urine metabolic analysis comprehensively reveals the disease status for kidney diseases in particular. Thus, the precise and convenient acquisition of metabolic molecular information from united biofluids is vitally important for clinical disease diagnosis and biomarker discovery. Laser desorption/ionization mass spectrometry (LDI-MS) presents various advantages in metabolic analysis; however, there remain challenges in ionization efficiency and MS signal reproducibility. Herein, we constructed a self-assembled hyperbranched black gold nanoarray (HyBrAuNA) assisted LDI-MS platform to profile serum united urine metabolic fingerprints (S-UMFs) for diagnosis of early stage renal cell carcinoma (RCC). The closely packed HyBrAuNA afforded strong electromagnetic field enhancement and high photothermal conversion efficacy, enabling effective ionization of low abundant metabolites for S-UMF collection. With a uniform nanoarray, the platform presented excellent reproducibility to ensure the accuracy of S-UMFs obtained in seconds. When it was combined with automated machine learning analysis of S-UMFs, early stage RCC patients were discriminated from the healthy controls with an area under the curve (AUC) > 0.99. Furthermore, we screened out a panel of 9 metabolites (4 from serum and 5 from urine) and related pathways toward early stage kidney tumor. In view of its high-throughput, fast analytical speed, and low sample consumption, our platform possesses potential in metabolic profiling of united biofluids for disease diagnosis and pathogenic mechanism exploration.

NDI based C2-symmetric Chiral Supramolecular Hydrogels Towards Enhanced Conductivity

To comprehend the significance of improved conductive properties in C2-symmetric hydrogels, it is vital to investigate how non-gelating achiral functional group isomers influence the conductivity of such supramolecular hydrogels, whereas understanding the major driving forces behind this regulatory process is first and foremost. Herein, we report a hydrogel system containing tryptophan-conjugated NDI as the backbone (L/D-NTrp), enabling effective supramolecular assembly with the bipyridyl functional group isomers. This co-assembly behavior results in materials with exceptional mechanical properties and high conductivities, surpassing most previously reported C2-symmetrical hydrogels, as well as the ability to form controlled morphologies. Notably, the co-hydrogels displayed an eight-fold increase in mechanical strength, making them more robust and resistant to deformation compared to the original gel. Additionally, all hydrogels exhibited favorable electrical conductivity, with the co-assembled hydrogels showcasing notable performance, making them a promising candidate for use in electronic devices and sensors. This report lays the foundation for further investigation into the properties and potential applications of L/D-NTrp compound in the range of fields, including drug delivery, tissue engineering, and electronics.

Dual-Color Real-Time Chemosensing of a Compartmentalized Reaction Network Involving Enzyme-Induced Membrane Permeation of Peptides

The design of synthetic systems with interrelated reaction sequences that model incipient biological complexity is limited by physicochemical tools that allow the direct monitoring of the individual processes in real-time. To mimic a simple digestion-resorption sequence, the authors have designed compartmentalized liposomal systems that incorporate extra- and intravesicular chemosensing ensembles. The extravesicular reporter pair consists of cucurbit[7]uril and methylene blue to monitor the enzymatic cleavage of short enkephalin-related peptides by thermolysin through a switch-off fluorescence response ("digestion"). Because the substrate is membrane-impermeable, but the dipeptide product is permeable, uptake of the latter into the pre-formed liposomes occurs as a follow-up process. The intravesicular chemosensing ensemble consists of i) cucurbit[8]uril, 2-anilinonaphthalene-6-sulfonic acid, and methyl viologen or ii) cucurbit[7]uril and berberine to monitor the uptake ("resorption") of the enzymatic products through the liposomal membranes by i) a switch-on or ii) a switch-off fluorescence response. The dyes are designed to allow selective optical excitation and read-out of the extra- and intravesicular dyes, which allow for dual-color chemosensing and, therefore, kinetic discrimination of the two sequential reactions.

Comprehensive Metabolic Fingerprints Characterize Neuromyelitis Optica Spectrum Disorder by Nanoparticle-Enhanced Laser Desorption/Ionization Mass Spectrometry

Timely screening of neuromyelitis optica spectrum disorder (NMOSD) and differential diagnosis from myelin oligodendrocyte glycoprotein associated disorder (MOGAD) are the keys to improving the quality of life of patients. Metabolic disturbance occurs with the development of NMOSD. Still, advanced tools are required to probe the metabolic phenotype of NMOSD. Here, we developed a fast nanoparticle-enhanced laser desorption/ionization mass spectrometry assay for multiplexing metabolic fingerprints (MFs) from trace plasma and cerebrospinal fluid (CSF) samples in 30 s. Machine learning of the plasma MFs achieved the timely screening of NMOSD from healthy donors with an area under receiver operator characteristic curve (AUROC) of 0.998, and it comprehensively revealed the dysregulated neurotransmitter and energy metabolisms. Combining comprehensive MFs from both plasma and CSF, we constructed an integrated panel for differential diagnosis of NMOSD versus MOGAD with an AUROC of 0.923. This approach demonstrated performance superior to that of human experts in classifying two diseases, especially in antibody assay-limited regions. Together, this approach provides an advanced nanomaterial-based tool for identifying vulnerable populations below the antibody threshold of aquaporin-4 positivity.

Ratiometric electrochemical OR gate assay for NSCLC-derived exosomes

Non-small cell lung cancer (NSCLC) is the most common pathological type of LC and ranks as the leading cause of cancer deaths. Circulating exosomes have emerged as a valuable biomarker for the diagnosis of NSCLC, while the performance of current electrochemical assays for exosome detection is constrained by unsatisfactory sensitivity and specificity. Here we integrated a ratiometric biosensor with an OR logic gate to form an assay for surface protein profiling of exosomes from clinical serum samples. By using the specific aptamers for recognition of clinically validated biomarkers (EpCAM and CEA), the assay enabled ultrasensitive detection of trace levels of NSCLC-derived exosomes in complex serum samples (15.1 particles μL^-1 within a linear range of 10²-10⁸ particles μL^-1). The assay outperformed the analysis of six serum biomarkers for the accurate diagnosis, staging, and prognosis of NSCLC, displaying a diagnostic sensitivity of 93.3% even at an early stage (Stage I). The assay provides an advanced tool for exosome quantification and facilitates exosome-based liquid biopsies for cancer management in clinics.