In this work, we demonstrate the significance of defined surface chemistry in synthesizing luminescent carbon nanomaterials (LCN) with the capability to perform dual functions (i.e., diagnostic imaging and therapy). The surface chemistry of LCN has been tailored to achieve two different varieties: one that has a thermoresponsive polymer and aids in the controlled delivery of drugs, and the other that has fluorescence emission both in the visible and near-infrared (NIR) region and can be explored for advanced diagnostic modes. Although these particles are synthesized using simple, yet scalable hydrothermal methods, they exhibit remarkable stability, photoluminescence and biocompatibility. The photoluminescence properties of these materials are tunable through careful choice of surface-passivating agents and can be exploited for both visible and NIR imaging. Here the synthetic strategy demonstrates the possibility to incorporate a potent antimetastatic agent for inhibiting melanomas in vitro. Since both particles are Raman active, their dispersion on skin surface is reported with Raman imaging and utilizing photoluminescence, their depth penetration is analysed using fluorescence 3D imaging. Our results indicate a new generation of tunable carbon-based probes for diagnosis, therapy or both.

Signal transducer and activator of transcription factor 3 (STAT-3) is known to be overexpressed in cancer stem cells. Poor solubility and variable drug absorption are linked to low bioavailability and decreased efficacy. Many of the drugs regulating STAT-3 expression lack aqueous solubility; hence hindering efficient bioavailability. A theranostics nanoplatform based on luminescent carbon particles decorated with cucurbit[6]uril is introduced for enhancing the solubility of niclosamide, a STAT-3 inhibitor. The host–guest chemistry between cucurbit[6]uril and niclosamide makes the delivery of the hydrophobic drug feasible while carbon nanoparticles enhance cellular internalization. Extensive physicochemical characterizations confirm successful synthesis. Subsequently, the host–guest chemistry of niclosamide and cucurbit[6]uril is studied experimentally and computationally. In vitro assessments in human breast cancer cells indicate approximately twofold enhancement in IC50 of drug. Fourier transform infrared and fluorescence imaging demonstrate efficient cellular internalization. Furthermore, the catalytic biodegradation of the nanoplatforms occur upon exposure to human myeloperoxidase in short time. In vivo studies on athymic mice with MCF-7 xenograft indicate the size of tumor in the treatment group is half of the controls after 40 d. Immunohistochemistry corroborates the downregulation of STAT-3 phosphorylation. Overall, the host–guest chemistry on nanocarbon acts as a novel arsenal for STAT-3 inhibition.

Typically, multiplexing high nanoparticle uptake, imaging, and therapy requires careful integration of three different functions of a multiscale molecular-particle assembly. Here, we present a simpler approach to multiplexing by utilizing one component of the system for multiple functions. Specifically, we successfully synthesized and characterized colloidal carotene carbon nanoparticle (C3-NP), in which a single functional molecule served a threefold purpose. First, the presence of carotene moieties promoted the passage of the particle through the cell membrane and into the cells. Second, the ligand acted as a potent detrimental moiety for cancer cells and, finally, the ligands produced optical contrast for robust microscopic detection in complex cellular environments. In comparative tests, C3-NP were found to provide effective intracellular delivery that enables both robust detection at cellular and tissue level and presents significant therapeutic potential without altering the mechanism of intracellular action of β-carotene. Surface coating of C3 with phospholipid was used to generate C3-Lipocoat nanoparticles with further improved function and biocompatibility, paving the path to eventual in vivo studies.

Nearfield spectroscopic imaging techniques can be a powerful tool to map both cellular ultrastructure and molecular composition simultaneously but are currently limited in measurement capability. Resonance enhanced (RE) atomic force microscopy infrared (AFM-IR) spectroscopic imaging offers high-sensitivity measurements, for example, but probe-sample mechanical coupling, nonmolecular optical gradient forces, and noise overwhelm recorded chemical signals. Here, we analyze the key factors limiting AFM-IR measurements and propose an instrument design that enables high-sensitivity nanoscale IR imaging by combining null-deflection measurements with RE sensitivity. Our developed null-deflection scanning probe IR (NDIR) spectroscopic imaging provides ∼24× improvement in signal-to-noise ratio (SNR) compared with the state of the art, enables optimal signal recording by combining cantilever resonance with maximum laser power, and reduces background nonmolecular signals for improved analytical accuracy. We demonstrate the use of these properties for high-sensitivity, hyperspectral imaging of chemical domains in 100-nm-thick sections of cellular acini of a prototypical cancer model cell line, MCF-10A. NDIR chemical imaging enables facile recording of label-free, chemically accurate, high-SNR vibrational spectroscopic data from nanoscale domains, paving the path for routine studies of biomedical, forensic, and materials samples.

Context.— Myocardial fibrosis underpins a number of cardiovascular conditions and is difficult to identify with standard histologic techniques. Challenges include imaging, defining an objective threshold for classifying fibrosis as mild or severe, as well as understanding the molecular basis for these changes. Objective.— To develop a novel, rapid, label-free approach to accurately measure and quantify the extent of fibrosis in cardiac tissue using infrared spectroscopic imaging. Design.— We performed infrared spectroscopic imaging and combined that with advanced machine learning–based algorithms to assess fibrosis in 15 samples from patients belonging to the following 3 classes: (1) nonpathologic (control) donor hearts; (2) patients receiving transplant; and (3) tissue from patients undergoing implantation of ventricular assist device. Results.— Our results show excellent sensitivity and accuracy for detecting myocardial fibrosis as demonstrated by high area under the curve of 0.998 in the receiver-operating characteristic curve measured from infrared imaging. Fibrosis of various morphologic subtypes are then demonstrated with virtually generated picrosirius red images, which show good visual and quantitative agreement (correlation coefficient = 0.92, ρ = 7.76 × 10−15) with stained images of the same sections. Underlying molecular composition of the different subtypes were investigated with infrared spectra showing reproducible differences presumably arising from differences in collagen subtypes and/or crosslinking. Conclusions.— Infrared imaging can be a powerful tool in studying myocardial fibrosis and gleaning insights into the underlying chemical changes that accompany it. Emerging methods suggest that the proposed approach is compatible with conventional optical microscopy and its consistency makes it translatable to the clinical setting for real-time diagnoses as well as for objective and quantitative research.

Freeform 3D printing combined with sacrificial molding promises to lead advances in production of highly complex tubular systems for biomedical applications. Here we leverage a purpose-built isomalt 3D printer to generate complex channel geometries in hydrogels which would be inaccessible with other techniques. To control the dissolution of the scaffold, we propose an enabling technology consisting of an automated nebulizer coating system which applies octadecane to isomalt scaffolds. Octadecane, a saturated hydrocarbon, protects the rigid mold from dissolution and provides ample time for gels to set around the sacrificial structure. With a simplified model of the nebulizer system, the robotic motion was optimized for uniform coating. Using a combination of stimulated Raman scattering (SRS) microscopy and X-ray computed tomography, the coating was characterized to assess surface roughness and consistency. Colorimetric measurements of dissolution rates allowed optimization of sprayer parameters, yielding a decrease in dissolution rates by at least 4 orders of magnitude. High fidelity channels are ensured by surfactant treatment of the coating, which prevents bubbles from clinging to the surface. Spontaneous Raman scattering microspectroscopy and white light microscopy indicate cleared channels are free of octadecane following gentle flushing. The capabilities of the workflow are highlighted with several complex channel architectures including helices, blind channels, and multiple independent channels within polyacrylamide hydrogels of varying stiffnesses.

Precise freeform microchannels within an aqueous environment have several biomedical applications but remain a challenge to fabricate. Carbohydrate glass materials have shown potential for threedimensionally (3D) printing precise, microscale structures and are suitable as a sacrificial material to reconstruct complex channel architectures, but due to the rapid dissolution kinetics in hydrogels and the aqueous environment, protective coatings are required. Here, conformal coatings were applied to carbohydrate structures via surface-initiated photopolymerization (SIP) by incorporating a photoinitiator (PI) into freeform 3D printed isomalt structures using a custom 3D printer. Structures were then immersed into a photocurable prepolymer bath and exposed to light for reaction initiation. To achieve uniform distribution of photoinitiator molecules in 3D printed constructs, miscibility between commercial photoinitiators and isomalt was modeled using the group contribution method. A dye-based, type-two photoinitiator, Eosin Y disodium salt (EY), was selected for its miscibility with isomalt and stability under high temperature. A previously described Eosin Y (EY)/triethanolamine (TEA) radical polymerization system was used to polymerize poly(ethylene glycol) diacrylate (PEGDA). Attenuated total reflectance−Fourier transform infrared (ATR-FTIR), surface morphology, and swelling ratio characterizations via SIP were performed. Coatings around freeform structures and solid surfaces were presented to demonstrate the capability of coating complex architectures. This coating method should facilitate the application of 3D sacrificial molding in a variety of hydrogels toward building biomimetic vascular constructs.

Rapid measurements of protein and oil content are important for a variety of uses, from sorting of soybeans at the point of harvest to feedback during soybean meal production. In this study, our goal is to develop a simple protocol to permit rapid and robust quantitative prediction of soybean constituents using transmission Raman spectroscopy (TRS). To develop this approach, we systematically varied the various elements of the measurement process to provide a diverse test bed. First, we utilized an in-house-built benchtop TRS instrument such that suitable optical configurations could be rapidly deployed and analyzed for experimental data collection for individual soybean grains. Second, we also utilized three different soybean varieties with relatively low (33.97%), medium (36.98%), and high protein (41.23%) contents to test the development process. Third, samples from each variety were prepared using whole bean and three different sample treatments (i.e., ground bean, whole meal, and ground meal). In each case, we modeled the data obtained using partial least squares (PLS) regression and assessed spectral metric-based multiple linear regression (metric-MLR) approaches to build robust prediction models. The metric-MLR models showed lower root mean square errors (RMSEPs), and hence better prediction, compared to corresponding classical PLS regression models for both bulk protein and oil for all treatment types. Comparing different sample preparation approaches, a lower RMSEPs was observed for whole meal treatment and thus the metric-MLR modeling with ground meal treatment was considered to be optimal protocol for bulk protein and oil prediction in soybean, with RMSEP values of 1.15 ± 0.04 (R2 = 0.87) and 0.80 ± 0.02 (R2 = 0.87) for bulk protein and oil, respectively. These predictions were nearly two- to threefold better (i.e., lower RMSEPs) than the corresponding NIR spectroscopy measurements (i.e., secondary gold standards in grain industry). For content prediction in whole soybean, incorporating physical attributes of individual grains in metric-MLR approach show up to 22% improvement in bulk protein and a relatively mild (up to ∼5%) improvement in bulk oil prediction. The unique combination of metric-MLR modeling approach (which is rare in the field of grain analysis) and sample treatments resulted in improved prediction models; using the physical attributes of individual grains is suggested as a novel measure for improving accuracy in prediction.