The ability to image tissues in three dimensions (3D) with label-free molecular contrast at the mesoscale would be a valuable capability in biology and biomedicine. Here, we introduce Raman spectral projection tomography (RSPT) for volumetric molecular imaging with optical sub-millimeter spatial resolution. We have developed a RSPT imaging instrument capable of providing 3D molecular contrast in transparent and semi-transparent samples. We also created a computational pipeline for multivariate reconstruction to extract label-free spatial molecular information from Raman projection data. Using these tools, we demonstrate imaging and visualization of phantoms of various complex shapes with label-free molecular contrast. Finally, we apply RSPT as a tool for imaging of molecular gradients and extracellular matrix heterogeneities in fixed and living tissue-engineered constructs and explanted native cartilage tissues. We show that there exists a favorable balance wherein employing Raman spectroscopy, with its advantages in live cell imaging and label-free molecular contrast, outweighs the reduction in imaging resolution and blurring caused by diffuse photon propagation. Thus, RSPT imaging opens new possibilities for label-free molecular monitoring of tissues.

Current techniques for monitoring disease progression and testing drug efficacy in animal models of inflammatory arthritis are either destructive, time-consuming, subjective, or require ionizing radiation. To accommodate this, we have developed a non-invasive and label-free optical system based on Raman spectroscopy for monitoring tissue alterations in rodent models of arthritis at the biomolecular level. To test different sampling geometries, the system was designed to collect both transmission and reflection mode spectra. Mice with collagen antibody-induced arthritis and controls were subject to in vivo Raman spectroscopy at the tibiotarsal joint every 3 days for 14 days. Raman-derived measures of bone content correlated well with micro-computed tomography bone mineral densities. This allowed for time-resolved quantitation of bone densities, which indicated gradual bone erosion in mice with arthritis. Inflammatory pannus formation, bone erosion, and bone marrow inflammation were confirmed by histological analysis. In addition, using library-based spectral decomposition, we quantified the progression of bone and soft tissue components. In general, the tissue components followed significantly different tendencies in mice developing arthritis compared to the control group in line with the histological analysis. In total, this demonstrates Raman spectroscopy as a versatile technique for monitoring alterations to both mineralized and soft tissues simultaneously in rodent models of musculoskeletal disorders. Furthermore, the technique presented herein allows for objective repeated within-animal measurements potentially refining and reducing the use of animals in research while improving the development of novel antiarthritic therapeutics.

Biosensors have a recognition element that detects a bioanalyte as well as a transducer that transfers the measured physicochemical properties into an electric signal, which is amplified, processed, and depicted on a user interface and usually stored in a data storage system. Such biosensors can be used in a broad range of applications, from personalized medicine to drug discovery, and from food safety to plant disease diagnosis. Portable biosensors are often based on microfluidic systems or micro-electromechanical systems (MEMS), measuring physical or chemical parameters. In spite of their importance for diverse applications, there are still several limits regarding the portability of biosensors, which is often necessary. Besides the required miniaturization of the components and the limited lifetime of some biological reagents, sample preparation and handling can be problematic. This review gives an overview of recent biosensor research, concentrating on optical measurements, and shows the possibilities and limits of the biosensors developed during the last few years.

Nanofiber mats with a high surface-to-volume ratio can be prepared by electrospinning. The Porosity is sometimes reported to be tunable by blending different materials, e.g., water-soluble poly(ethylene oxide) (PEO) with not water-soluble poly(acrylonitrile) (PAN). Here, nanofiber mats were electrospun from different PAN:PEO ratios, using a wire-based electrospinning machine “Nanospider Lab”. Investigations of the as-spun nanofiber mats as well as of membranes after washing off the water-soluble PEO by scanning electron microscopy (SEM) revealed severe differences in the nanofiber mat morphologies, such as varying fiber diameters and especially non-fibrous areas in the carbonized nanofiber mats, depending on the amount of PEO in the nanofiber mat as well as the molecular weight of the PEO. Similarly, the ratio and molecular weight of PEO influenced the results of stabilization and carbonization. This paper discusses the possibility of tailoring nanofiber porosity for the potential use of PAN nanofiber mats in tissue engineering, filtration, and other applications.

The commercial use of Metarhizium anisopliae blastospores is significantly limited by their poor storage stability, mainly due to viability loss over time. Understanding the mechanisms underlying this decline is therefore essential to improve blastospore-based products. In this study, we investigated factors associated with viability loss in blastospores dried to two water activity levels, a _w = 0.1 (BS01) and a _w = 0.3 (BS03), representing more severely and moderately desiccated states, respectively. Samples were stored at 28 °C for 90 days and analyzed every 30 days using viability assays, flow cytometry, protein oxidation analysis, GC–MS, HPLC, and Raman spectroscopy. Viability declined progressively by approximately three orders of magnitude during storage, with BS01 showing a markedly faster reduction than BS03 during the first 30 days. Early storage stages were characterized by high oxidative stress, including elevated reactive oxygen species, lipid peroxidation, and impaired membrane integrity, all of which declined over time as metabolic activity decreased. In contrast, protein carbonylation increased continuously, reaching 11.02 ± 2.23 nmol/mg protein after 90 days. Metabolic analysis of BS01 revealed disrupted cellular homeostasis, including trehalose depletion and glucose accumulation, suggesting impaired metabolic capacity. Raman spectroscopy confirmed progressive molecular alterations in proteins, lipids, and polysaccharides. Together, these findings indicate that cumulative oxidative damage, particularly irreversible protein carbonylation, combined with progressive metabolic dysfunction, is a central driver of blastospore viability loss during storage.

Raman microscopy is a label-free, non-destructive imaging tool for spatially resolved chemical fingerprinting. Its powerful ability to reveal molecular information has driven rapid growth in applications across fields as varied as materials science, environmental analysis, and biomedical research. Despite its versatility, the accessibility of Raman microscopy is limited by expensive commercial setups and the technical barriers faced by researchers attempting to build custom systems. Here, we introduce an Open Raman Microscopy (ORM) framework based on a readily accessible modular microscopy platform. The ORM platform provides configurations for both high-throughput imaging and confocal imaging. We developed a dedicated python-based control and acquisition software, the ORM-Integrated Raman and Imaging Software (ORM-IRIS) designed to accommodate modular integration and control of components, including the laser source, spectrometer, and translational stages. Implemented across three institutions we demonstrate the ORM platform for high-throughput imaging of articular cartilage tissue, confocal three-dimensional imaging of a zebrafish embryo, and imaging of gold colloid decorated surfaces for surface enhanced Raman spectroscopy. Together, this open-source hardware and software framework enhances the accessibility of Raman microscopy across an expanding range of scientific applications.