Raman spectroscopy has revolutionized the field of chemical biology by providing detailed chemical and compositional information with minimal sample preparation. Despite its advantages, the technique suffers from low throughput due to the weak Raman effect, necessitating long acquisition times and expensive equipment. This limitation is particularly acute in time-sensitive applications like bioprocess monitoring and dynamic studies. Compressive sensing offers a promising solution by reducing the burden on measurement hardware, lowering costs, and decreasing measurement times. It allows for the collection of sparse data, which can be computationally reconstructed later. This paper explores the practical application of compressive sensing in spontaneous Raman spectroscopy across various biological samples. We demonstrate its benefits in scenarios requiring portable hardware, rapid acquisition, and minimal storage, such as skin hydration prediction and cellular studies involving drug molecules. Our findings highlight the potential of compressive sensing to overcome traditional limitations of Raman spectroscopy, paving the way for broader adoption in biological research and clinical diagnostics.

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.

AbstractSurface‐enhanced Raman spectroscopy (SERS) possesses exquisite molecular‐specific properties with single‐molecule sensitivity. Yet, translation of SERS into a quantitative analysis technique remains elusive owing to considerable fluctuation of the SERS intensity, which can be ascribed to the SERS uncertainty principle, a tradeoff between “reproducibility” and “enhancement”. To provide a potential solution, herein, an integrated multiplexed SERS biosensing strategy is proposed, which features two distinct advantages. First, a subwavelength‐structured plasmonic metasurface consisting of alternately stacked metal–dielectric pyramidal meta‐atoms is fabricated and could provide simultaneously enhanced electric and magnetic fields to enable spatially extended and weakly wavelength‐dependent SERS. Second, nanomechanical perturbations are harnessed to transduce signals in the form of SERS frequency shifts, which are not directly affected by the SERS uncertainty principle. By also employing 3D printing methods, a proof‐of‐concept study of multiplexed detection of a panel of serum cardiac biomarkers for acute myocardial infarction is provided. Success in the development of both the electric and magnetic fields‐active plasmonic metasurfaces could transform future designs of SERS substrates with newly endowed functionalities, and frequency shift‐based SERS multiplexing could open new opportunities to develop innovative quantitative optical techniques for applications in chemistry, biology, and medicine.

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.

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.

During malaria infection, Plasmodium sporozoites, the fast-moving stage of the parasite, are injected by a mosquito into the skin of the mammalian host. In the skin, sporozoites need to migrate through the dermal tissue to enter the blood vessel. Sporozoite motility is critical for infection but not well understood. Here, we used collagen hydrogels with tunable fiber structures, as an in vitro model for the skin. After injecting sporozoites into the hydrogel, we analyzed their motility in three-dimension (3D). We found that sporozoites demonstrated chiral motility, in that they mostly follow right-handed helical trajectories. In high-concentration collagen gel, sporozoites have lower instantaneous speed, but exhibit straighter tracks compared to low-concentration collagen gel, which leads to longer net displacement and faster dissemination. Taken together, our study indicates an inner mechanism for sporozoites to adapt to the environment, which could help with their successful exit from the skin tissue.

While surface-enhanced Raman spectroscopy (SERS) has proved itself as a powerful tool in the analytical domain, its capability hinges on, and therefore, is governed by the interaction between molecules and plasmonic hotspots on nanostructured metallic substrates. Yet, the highly dynamic and complex molecule-metal interactions give rise to pronounced SERS signal fluctuations, compromising quantitative analysis at ultralow molecular concentrations. Rather than overcoming SERS signal fluctuations, the recently introduced digital SERS approach takes full advantage of their stochastic nature and allows digitalized visualization of SERS events at the single pixel level based on a predefined signal threshold, significantly pushing down the lowest detectable molecular concentration. Nevertheless, extending digital SERS for routine molecular analysis requires superior two-dimensional plasmonic substrates. Herein, we introduce a plasmonic gold prism array for digital SERS sensing. As opposed to nanostructured metallic arrays with similar geometry where the vertex and edge modes dominate, the gold prism array displays strong scattering as well as pronounced surface roughness and nanoparticle-like surface features, thus supporting additional plasmonic enhancements beyond the vertex and edge modes. Using 4-aminothiophenol as a model molecule, we first verify the counterintuitive distribution of SERS hotspots at the center of a gold prism instead of its vertices, and further demonstrate digital SERS sensing at the femtomolar level. We envision that the gold prism array could serve as a superior plasmonic platform for a wide range of digital SERS applications in diagnostics, environmental monitoring, and food safety.

Ordered plasmonic nanoparticle arrays are highly desirable for optical sensing as they provide uniformly distributed plasmonic hotspots due to their periodic order and near-field coupling. Anisotropic-shaped bimetallic nanoparticles are of particular interest, as their hybridized plasmonic modes enable precise tuning of plasmonic resonance and optical responses. However, the controlled assembly of large-scale arrays of bimetallic nanoparticles with uniformly distributed hotspots remains a challenge. In this study, we present a highly robust and reproducible method for creating large-area vertically aligned arrays of bimetallic Au-Ag nanorods by epitaxially growing Ag over preassembled Au nanorods. Structural characterization using electron microscopy and X-ray photoelectron spectroscopy confirms the formation of a uniform thin layer of Ag, creating a bimetallic Au-Ag nanorod array. We also demonstrate the efficacy of the designed nanoarrays for surface-enhanced Raman scattering (SERS) spectroscopy. Our experimental and computational studies show considerably enhanced optical responses of bimetallic Au-Ag nanorods compared to their monometallic counterparts. The scalability, cost-effectiveness, and reproducibility of this method make it a versatile platform for creating various structures by varying guest nanoparticles in suspensions with broad applications in biomedical research, food safety surveillance, and environmental monitoring.

Raman spectroscopy (RS) has emerged as a novel optical imaging modality by identifying molecular species through their bond vibrations, offering high specificity and sensitivity in molecule detection. However, its application in intracellular molecular probing has been limited due to challenges in combining vibrational tags with functional probes. DNA nanostructures, known for their high programmability, have been instrumental in fields like biomedicine and nanofabrication. So far, their ability to customize Raman signals remains largely untapped. In this study, a new class of Raman active DNA origami-based hybrid nanodevice (ND) for targeted cancer cell drug delivery and imaging is engineered. The ND is specifically engineered for metastatic prostate cancer treatment, featuring a legumain enzyme-responsive sequence for the controlled release of the chemotherapeutic agent doxorubicin. Integrating RS with precise targeting, the ND enables imaging of aggressive cancer cells and efficient drug delivery with minimal off-target effects. The developed device offers stimuli-responsive behavior, enhanced stability, exceptional tunability, and potent targeting abilities, positioning it as a highly promising strategy for advancing precision cancer imaging and therapy.

Plasmonic nanomaterials bearing targeting ligands are of great interest for surface-enhanced Raman scattering (SERS)-based bioimaging applications. However, the practical utility of SERS-based imaging strategies has been hindered by the lack of a straightforward method to synthesize highly sensitive SERS-active nanostructures with high yield and efficiency. In this work, leveraging DNA origami principles, we report the first-in-class design of a SERS-based plasmonically coupled nanoprobe for targeted cancer imaging (SPECTRA). The nanoprobe harnesses a cancer cell targeting DNA aptamer sequence and vibrational tag with stretching frequency in the cell-silent Raman window. Through the integration of aptamer sequence specific for DU145 cells, we show the unique capabilities of SPECTRA for targeted imaging of DU145 cells. Our results demonstrate that the scalability, cost-effectiveness, and reproducibility of this method of fabrication of SERS nanoprobes can serve as a versatile platform for creating nanoprobes with broad applications in the fields of cancer biology and biomedical imaging.

Quantitative phase imaging (QPI) is a powerful optical imaging modality for label-free, rapid, and three-dimen-sional (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-re-sponsive peptide sequences. The nanoprobes specifically aggre-gated 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.

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 complex-ities 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.

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.

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.

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.

The repository features .xls and .txt worksheets including all the data used through this work and reported in the manuscript figures and graphs. More precisely, we included the following: Figure 2. Raw pixel-wise signals detected in NLO images of TIS cells control cells that were used to perform the colocalization graphs and analyses reported. We describe the average colocalization of SRS and F-CARS signals, and TPEF and E-CARS signals, in both phenotypes. Figure 4. Raw data from image analyses of TPEF and SRS channels of multimodal NLO images, divided in 5 different time points over the therapy follow-up period. The data describe the early rearrangement of mitochondria (TPEF) and lipid vesicles (SRS) in TIS cells, with respect to control counterparts. Figure 6. Raw data from image analyses of QPI images, divided in 4 different time points over the therapy follow-up period. The data describe the early morphological modifications of TIS cells, with respect to control counterparts.

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.