Label-free plasmonic spectral profiling of serum DNA.

Genetic and epigenetic modifications are linked to the activation of oncogenes and inactivation of tumor suppressor genes. Likewise, the associated molecular alternations can best inform precision medicine for personalized tumor treatment. Therefore, performing characterization of genetic and epigenetic alternations at the molecular level represents a crucial step in early diagnosis and/or therapeutics of cancer. However, the prevailing methods for DNA analysis involve a series of tedious and complicated steps, in which important genetic and epigenetic information could be lost or altered. To provide a potential approach for non-invasive, direct, and efficient DNA analysis, herein, we present a promising strategy for label-free molecular profiling of serum DNA in its pristine form by fusing surface-enhanced Raman spectroscopy with machine learning on a superior plasmonic nanostructured platform. Using DNA methylation and single-point mutation as two case studies, the presented strategy allows a well-balanced sensitive and specific detection of epigenetic and genetic changes at the single-nucleotide level in serum. We envision the presented label-free strategy could serve as a versatile tool for direct molecular profiling in pristine forms of a wide range of biological markers and aid biomedical diagnostics as well as therapeutics.

Engineering vascularized skin-mimetic phantom for non-invasive Raman spectroscopy.

Recent advances in Raman spectroscopy have shown great potential for non-invasive analyte sensing, but the lack of a standardized optical phantom for these measurements has hindered further progress. While many research groups have developed optical phantoms that mimic bulk optical absorption and scattering, these materials typically have strong Raman scattering, making it difficult to distinguish metabolite signals. As a result, solid tissue phantoms for spectroscopy have been limited to highly scattering tissues such as bones and calcifications, and metabolite sensing has been primarily performed using liquid tissue phantoms. To address this issue, we have developed a layered skin-mimetic phantom that can support metabolite sensing through Raman spectroscopy. Our approach incorporates millifluidic vasculature that mimics blood vessels to allow for diffusion akin to metabolite diffusion in the skin. Furthermore, our skin phantoms are mechanically mimetic, providing an ideal model for development of minimally invasive optical techniques. By providing a standardized platform for measuring metabolites, our approach has the potential to facilitate critical developments in spectroscopic techniques and improve our understanding of metabolite dynamics in vivo.

Quantitative Detection of Thyroid-Stimulating Hormone in Patient Samples with a Nanomechanical Single-Antibody Spectro-Immunoassay.

Functional disorders of the thyroid remain a global challenge and have profound impacts on human health. Serving as the barometer for thyroid function, thyroid-stimulating hormone (TSH) is considered the single most useful test of thyroid function. However, the prevailing TSH immunoassays rely on two types of antibodies in a sandwich format. The requirement of repeated incubation and washing further complicates the issue, making it unable to meet the requirements of the shifting public health landscape that demands rapid, sensitive, and low-cost TSH tests. Herein, a systematic study is performed to investigate the clinical translational potential of a single antibody-based biosensing platform for the TSH test. The biosensing platform leverages Raman spectral variations induced by the interaction between a TSH antigen and a Raman molecule-conjugated TSH antibody. In conjunction with machine learning, it allows TSH concentrations in various patient samples to be predicted with high accuracy and precision, which is robust against substrate-to-substrate, intra-substrate, and day-to-day variations. It is envisioned that the simplicity and generalizability of this single-antibody immunoassay coupled with the demonstrated performance in patient samples pave the way for it to be widely applied in clinical settings for low-cost detection of hormones, other molecular biomarkers, DNA, RNA, and pathogens.

A Smart Intracellular Self-Assembling Bioorthogonal Raman Active Nanoprobe for Targeted Tumor Imaging.

Inspired by the principle of in situ self-assembly, the development of enzyme-activated molecular nanoprobes can have a profound impact on targeted tumor detection. However, despite their intrinsic promise, obtaining an optical readout of enzyme activity with high specificity in native milieu has proven to be challenging. Here, a fundamentally new class of Raman-active self-assembling bioorthogonal enzyme recognition (nanoSABER) probes for targeted tumor imaging is reported. This class of Raman probes presents narrow spectral bands reflecting their vibrational fingerprints and offers an attractive solution for optical imaging at different bio-organization levels. The optical beacon harnesses an enzyme-responsive peptide sequence, unique tumor-penetrating properties, and vibrational tags with stretching frequencies in the cell-silent Raman window. The design of nanoSABER is tailored and engineered to transform into a supramolecular structure exhibiting distinct vibrational signatures in presence of target enzyme, creating a direct causality between enzyme activity and Raman signal. Through the integration of substrate-specific for tumor-associated enzyme legumain, unique capabilities of nanoSABER for imaging enzyme activity at molecular, cellular, and tissue levels in combination with machine learning models are shown. These results demonstrate that the nanoSABER probe may serve as a versatile platform for Raman-based recognition of tumor aggressiveness, drug accumulation, and therapeutic response.

Noninvasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells.

Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells.

Shining Light on Osteoarthritis: Spatially Offset Raman Spectroscopy as a Window into Cartilage Health.

Articular cartilage is a complex tissue, and early detection of osteoarthritis (OA) is crucial for effective treatment. However, current imaging modalities lack molecular specificity and primarily detect late-stage changes. In this study, we propose the use of Spatially Offset Raman Spectroscopy (SORS) for non-invasive, depth-dependent, and molecular-specific diagnostics of articular cartilage. We demonstrate the potential of SORS to penetrate deep layers of cartilage, providing a comprehensive understanding of disease progression. Our SORS measurements were characterized and validated through mechanical and histological techniques, revealing strong correlations between spectroscopic measurements and both Young's modulus and depth of cartilage damage. By longitudinally monitoring enzymatically degraded condyles, we further developed a depth-dependent damage-tracking method. Our analysis revealed distinct components related to sample depth and glycosaminoglycan (GAG) changes, offering a comprehensive picture of cartilage health. Collectively, these findings highlight the potential of SORS as a valuable tool for enhancing OA management and improving patient outcomes.

Targeted Enzyme Activity Imaging with Quantitative Phase Microscopy.

Quantitative phase imaging (QPI) is a powerful optical imaging modality for label-free, rapid, and three-dimensional (3D) monitoring of cells and tissues. However, molecular imaging of important intracellular biomolecules such as enzymes remains a largely unexplored area for QPI. Herein, we introduce a fundamentally new approach by designing QPI contrast agents that allow sensitive detection of intracellular biomolecules. We report a new class of bio-orthogonal QPI-nanoprobes for in situ high-contrast refractive index (RI) imaging of enzyme activity. The nanoprobes feature silica nanoparticles (SiO2 NPs) having higher RI than endogenous cellular components and surface-anchored cyanobenzothiazole-cysteine (CBT-Cys) conjugated enzyme-responsive peptide sequences. The nanoprobes specifically aggregated in cells with target enzyme activity, increasing intracellular RI and enabling precise visualization of intracellular enzyme activity. We envision that this general design of QPI-nanoprobes could open doors for spatial-temporal mapping of enzyme activity with direct implications for disease diagnosis and evaluating the therapeutic efficacy.

DNA-Patched Nanoparticles for the Self-Assembly of Colloidal Metamaterials.

Colloidal metamaterials are highly desired artificial materials that recapitulate the structure of simple molecules. They exhibit exceptional functionalities conferred by the organization of and specific interaction among constituent elements. Harvesting such exquisite attributes for potential applications necessitates establishing precise control over their structural configuration with high precision. Yet, creating molecule-like small clusters of colloidal metamaterials remains profoundly challenging, as a lack of regioselectively encoded surface chemical heterogeneity prevents specific recognition interactions. Herein, we report a new strategy by harnessing magnetic-bead-assisted DNA cluster transferring to create discretely DNA cluster-patched nanoparticles for the self-assembly of colloidal metamaterials. This strategy affords broad generalizability and scalability for robustly patching DNA clusters on nanoparticles unconstrained by geometrical, dimensional, and compositional complexities commonly encountered in colloidal materials at the nano- and microscale. We direct judiciously patched nanoparticles into a wide variety of nanoassemblies and present a case study demonstrating the distinct metamaterial properties in enhancing the spontaneous emission of diamond nanoparticles. This newly invented strategy is readily implementable and extendable to construct a palette of structurally sophisticated and functionality-explicit architecture, paving the way for nanoscale manipulation of colloidal material functionalities with wide-ranging applications for biological sensing, optical engineering, and catalytic chemistry.

An Adaptive ORB-SLAM3 System for Outdoor Dynamic Environments.

Recent developments in robotics have heightened the need for visual SLAM. Dynamic objects are a major problem in visual SLAM which reduces the accuracy of localization due to the wrong epipolar geometry. This study set out to find a new method to address the low accuracy of visual SLAM in outdoor dynamic environments. We propose an adaptive feature point selection system for outdoor dynamic environments. Initially, we utilize YOLOv5s with the attention mechanism to obtain a priori dynamic objects in the scene. Then, feature points are selected using an adaptive feature point selector based on the number of a priori dynamic objects and the percentage of a priori dynamic objects occupied in the frame. Finally, dynamic regions are determined using a geometric method based on Lucas-Kanade optical flow and the RANSAC algorithm. We evaluate the accuracy of our system using the KITTI dataset, comparing it to various dynamic feature point selection strategies and DynaSLAM. Experiments show that our proposed system demonstrates a reduction in both absolute trajectory error and relative trajectory error, with a maximum reduction of 39% and 30%, respectively, compared to other systems.

Leveraging Nanomechanical Perturbations in Raman Spectro-Immunoassays to Design a Versatile Serum Biomarker Detection Platform.

While immunoassays are pivotal to medical diagnosis and bioanalytical chemistry, the current landscape of public health has catalyzed an important shift in the requirements of immunoassays that demand innovative solutions. For example, rapid, label-free, and low-cost screening of a given analyte is required to inform the best countermeasures to combat infectious diseases in a timely manner. Yet, the current design of immunoassays cannot accommodate such requirements as constraint by accumulative challenges, such as repeated incubation and washing, and the need of two types of antibodies in the sandwich format. To provide a potential solution, herein, a plasmonic Raman immunoassay with single-antibody, multivariate regression, and shift-of-peak strategies, coined as the PRISM assay, for serum biomarkers detection, is reported. The PRISM assay relies on Raman reporter-antibody conjugates to capture analytes on a plasmonic substrate. The ensuing nanomechanical perturbations to vibration of Raman reporters induce subtle but characteristic spectral changes that encode rich information related to the captured analytes. By fusing Raman spectroscopy and chemometric analysis, both Raman frequency shift- and multivariate regression models for sensitive detection of biomarkers are developed. The PRISM assay is expected to find a wide range of applications in clinical diagnosis, food safety surveillance, and environmental monitoring.

A Dual-Modal Single-Antibody Plasmonic Spectro-Immunoassay for Detection of Small Molecules.

Small molecules play a pivotal role in regulating physiological processes and serve as biomarkers to uncover pathological conditions and the effects of therapeutic treatments. However, it remains a significant challenge to detect small molecules given the size as compared to macromolecules. Recently, the newly emerging plasmonic immunoassays based on surface-enhanced Raman scattering (SERS) offer great promise to deliver extraordinary sensitivity. Nevertheless, they are limited by the intrinsic SERS intensity fluctuations associated with the SERS uncertainty principle. The single transducer that relies on the intensity change is also prone to false signals. Additionally, the prevailing sandwich immunoassay format proves less effective towards detecting small molecules. To circumvent these critical issues, a dual-modal single-antibody approach that synergizes both the intensity and shift of the peak-based immunoassay with Raman enhancement, coined as the INSPIRE assay, is developed for small molecules detection. With two independent transduction mechanisms, it allows better prediction of analyte concentration and attenuation of signal artifacts, providing a new and robust strategy for molecular analysis. With a proof-of-concept demonstration for detection of free T4 and testosterone in serum matrix, the authors envision that the INSPIRE assay could be expanded for a wide spectrum of applications in biomedical diagnosis, discovery of new biopharmaceuticals, food safety, and environmental monitoring.

Comparative Study on the Fungicidal Activity of Metallic MgO Nanoparticles and Macroscale MgO Against Soilborne Fungal Phytopathogens.

Engineered nanoparticles have provided a basis for innovative agricultural applications, specifically in plant disease management. In this interdisciplinary study, by conducting comparison studies using macroscale magnesium oxide (mMgO), we evaluated the fungicidal activity of MgO nanoparticles (nMgO) against soilborne Phytophthora nicotianae and Thielaviopsis basicola for the first time under laboratory and greenhouse conditions. In vitro studies revealed that nMgO could inhibit fungal growth and spore germination and impede sporangium development more efficiently than could macroscale equivalents. Indispensably, direct contact interactions between nanoparticles and fungal cells or nanoparticle adsorption thereof were found, subsequently provoking cell morphological changes by scanning electron microscopy/energy-dispersive spectrometry (SEM/EDS) and transmission electron microscopy (TEM). In addition, the disturbance of the zeta potential and accumulation of various modes of oxidative stress in nMgO-exposed fungal cells accounted for the underlying antifungal mechanism. In the greenhouse, approximately 36.58 and 42.35% decreases in tobacco black shank and black root rot disease, respectively, could testify to the efficiency by which 500 µg/ml of nMgO suppressed fungal invasion through root irrigation (the final control efficiency reached 50.20 and 62.10%, respectively) when compared with that of untreated controls or mMgO. This study will extend our understanding of nanoparticles potentially being adopted as an effective strategy for preventing diversified fungal infections in agricultural fields.

Hydroxycoumarins: New, effective plant-derived compounds reduce Ralstonia pseudosolanacearum populations and control tobacco bacterial wilt.

Plant wilt disease caused by the soilborne bacterial pathogen Ralstonia pseudosolanacearum is one of the most devastating plant diseases; however, no effective protection against this disease has been developed. Coumarins are important natural plant-derived compounds with a wide range of bioactivities and extensive applications in medicine and agriculture. In the present study, three hydroxycoumarins (Hycs), umbelliferone (UM), esculetin (ES) and daphnetin (DA) significantly inhibited the growth of R. pseudosolanacearum on solid medium in a concentration-dependent manner, and the minimum inhibitory concentration (MICs) of these compounds was 325  mg L-1, 125 mg L-1 and 75 mg L-1, respectively. The percentage of live cells of R. pseudosolanacearum when supplemented with UM, ES, and DA was 63.61%, 17.81% and 7.23%, respectively, which were significantly lower than the DMSO treatment with 92%. Furthermore, irrigating roots with hydroxycoumarins (Hycs) 24 h before inoculation with R. pseudosolanacearum significantly delayed the occurrence of tobacco bacterial wilt, with the control efficiency of the DA treatment (the most efficient of Hycs treatment) 80.03%, 69.83%, 59.19%, 45.49%, 44.12%, 38.27% at 6, 8, 10, 12, 14, and 16 days after inoculation, respectively. Compared with the DMSO treatment, the pathogen populations of tobacco stems supplemented with 100 mg L-1 DA were the lowest, with population significantly reduced by 22.46%, 27.34%, and 18.06% at 4, 7, and 10 days after inoculation, respectively. Based on this study, these Hycs could be applied as potential protective agents in the management of tobacco bacterial wilt.