Small interfering RNAs (siRNAs) have drawn particular attention for their ability to transiently and sequence-specifically silence target genes, not only for systemic but also for localized application. For bone regeneration, targeting inhibitory regulators by siRNAs offers opportunities to improve osteogenic-angiogenic coupling.Conventional experimental models often oversimplify this interaction as they fail to capture these multicellular tissue dynamics. To address this, we established a human three-dimensional co-culture model composed of osteogenic and vascular microtissues embedded in fibrin hydrogels to investigate siRNA effects on microtissue interaction.Local siRNA delivery to microtissues was achieved by oligomer-stabilized calcium phosphate nanoparticles (CaP-NP) loaded onto cross-linked gelatin microparticles (cGM). siRNA/CaP-NP-loaded cGM were assembled with human mesenchymal stem cells (hMSCs) to microtissues. This approach was demonstrated by silencing two antagonists with distinct expression profiles: Chordin, a low-abundance BMP inhibitor, and WWP-1, a highly expressed E3 ligase. Only Chordin siRNA improved the osteogenic-vascular cross-talk, whereas WWP-1 siRNA effects were limited to osteogenic effects. Next-generation sequencing (NGS) supported these results.We demonstrate that this co-culture platform permits systematic investigation of siRNA-mediated modulation of osteogenic-endothelial interactions, offering a relevant human model for preselecting therapeutic siRNA targets to advance vascularized bone tissue regeneration.

Crosslinked gelatin microparticles (cGM) are versatile biomaterials with applications in regenerative medicine, tissue engineering, and drug or gene delivery. In this study, we investigated the crosslinking process of pristine gelatin microparticles using new generation reactive anhydride-containing amphiphilic oligomers synthesized from stearyl acrylate, 4-acryloylmorpholine, and maleic anhydride at varying ratios. An optimal design of experiments (DoE) was employed, comprising three factors and three responses. The factors included the anhydride content applied per crosslinking reaction (AC), the volume of base, i.e. triethylamine (TEA), and the molecular anhydride distribution (MAD) of a given oligomer type, an indirect parameter reflecting the stoichiometric density of anhydride units along the oligomer chains. The responses consisted of the mean degree of crosslinking (DoC) of the particle batch, degree of swelling (DoS), and particle transparency (MT). Dynamic image analysis and light micrographs confirmed the spherical morphology of the crosslinked gelatin microparticles and demonstrated that the crosslinking step did not alter particle shape. Through DoE runs, cGM batches with a broad range of crosslinking densities (DoC: 34-79%) were achieved. AC exerted the strongest effect on DoC and DoC correlated with AC following a logarithmic regression. An overall correlation between DoC and DoS was evident, showing that higher crosslinking densities reduced particle swelling. The TEA volume applied during crosslinking indicated that only small amounts were still sufficient to obtain a wide range of DoC, which is a favorable outcome as minimizing TEA helps reduce potential adverse effects in the final material. Finally, through DoE study, we established that oligomer MAD as a critical material attribute for this process, as it significantly influenced all responses.

BackgroundPediatric and adult glioblastomas (GBM) represent biologically distinct entities requiring age-tailored therapeutic strategies. However, rapid and non-invasive methods to distinguish these molecular subtypes remain an unmet clinical need. This study evaluates the potential of confocal Raman spectroscopy combined with deep learning as a label-free diagnostic tool to differentiate pediatric from adult GBM based on intrinsic biochemical fingerprints.MethodsWe acquired n=1,382 Raman spectra from a cohort of six patient-derived GBM neurosphere cell lines, comprising a pediatric model (SF188) and five adult-origin lines. A multilayer perceptron (MLP) neural network was trained to classify spectra by age group. To ensure rigorous validation and generalizability, performance was assessed on a strictly held-out external test set (20% of data), completely excluded from model optimization.ResultsThe deep learning model successfully differentiated pediatric from adult GBM signatures with an overall accuracy of 83.6% and an ROC AUC of 0.855 on the independent test set. Spectral analysis revealed distinct vibrational modes, highlighting significant variations in lipid, protein, and nucleic acid content between age groups. Notably, the model achieved a high sensitivity for the pediatric phenotype (91.4% identification rate) .ConclusionThis proof-of-concept study demonstrates that Raman spectroscopy, augmented by deep learning, can identify age-related molecular variations in GBM without extrinsic labeling. By capturing the unique biochemical landscape of pediatric versus adult tumors, this approach lays the foundation for rapid, automated, and objective diagnostic workflows in precision neuro-oncology.

This study presents a novel experimental setup that couples high-performance liquid chromatography (HPLC) with a custom-built deep ultraviolet resonance Raman spectrometer (DUV-RRS) for the identification and quantification of analytes following chromatographic separation. For the first time, a liquid-core waveguide (LCW) was integrated into an HPLC-DUV-RRS system to enhance Raman signal intensity. A cost-efficient and ecofriendly deep UV pulsed laser was employed to achieve this advancement with an average output power of only 0.5 mW. The combination of LCW and DUV-RRS enables strong absorption of the excitation light by the target molecules due to the extended optical pathlength within the LCW. The system's performance was evaluated using two pharmaceutical agents, metformin and naproxen. The detector's sensitivity was found to be compounddependent. For metformin and naproxen, detection limits of 0.07 mu g and 0.20 mu g, respectively, were achieved on-column, representing a 3.5-fold and 1.2-fold improvement over previous setups without LCW integration, even though the exposure time of the Raman detector was reduced by a factor of up to 60. While metformin showed a linear correlation between Raman signal intensity and concentration at lower concentrations, no linear relationship could be observed for naproxen due to absorption effects. Nevertheless, partial least squares (PLS) analysis revealed a linear relationship between signal intensity and analyte concentration for both substances across the full tested concentration range. These findings demonstrate the potential of LCW-enhanced DUV-RRS as a sensitive and selective detection method in hyphenated analytical systems, particularly for analytes with favorable resonance Raman properties.

Personalized chemotherapy requires precise compounding and reliable quality control to assure therapeutic efficacy and safety. Raman spectroscopy offers a non-destructive and non-invasive method for the identification and quantitation of cytostatic drug substances, which could improve current quality assurance processes in hospital or community pharmacies. In this study, a dedicated Raman detector was developed that enables direct identification and measurement of cytostatic drug concentrations in aqueous liquids through closed primary packaging. Measurements were performed for cyclophosphamide and gemcitabine in clinically relevant concentrations (1 - 45 mg mL-1) using sealed infusion glass vials, filled syringes for bolus injections and infusion bags. Each concentration was analyzed at eight different positions. These measurement positions were chosen randomly to account for signal variability arising from local material variations, including inhomogeneities in wall thickness and curvature. For all tested drug substances and packaging types and materials, relative prediction errors remained within ±10% across the clinically relevant concentration range, with a RMSECV of 1.07 mg mL⁻¹ for cyclophosphamide and 0.54 mg mL⁻¹ for gemcitabine. As routine quality control of individually compounded antineoplastic formulations lacks standardized final-product verification, non-invasive through-container spectroscopic analysis offers the possibility to add identity and concentration confirmation without opening or sampling the CMR-classified formulation. This method preserves the integrity of the final drug product while reducing costs and the risk of occupational exposure for pharmacy personnel.

Injectable chitosan hydrogels, designed to emulate the extracellular matrix (ECM) in tissue engineering, are conventionally formed through physical gelation. This study aims to enhance stability and broaden the range of gel properties by adopting a covalent cross-linking approach. To achieve this, a series of hydrophilic oligomeric oligomers were synthesized, incorporating acryloyl morpholine (AMo) and reactive maleic anhydride (MA) in varying ratios, both with and without the hydrophobic comonomer pentaerythritol diacrylate monostearate (PEDAS). These oligomers, characterized by low molecular weight (Mn < 5000 Da) and differing anhydride content, were rheologically assessed for their ability to cross-link chitosan under physiological conditions. The resulting injectable oligomer-cross-linked chitosan hydrogels (iCsgel) exhibited substantial elastic strength (with an estimated E of up to 28 kPa). Furthermore, oligomer-cross-linking facilitated the production of chitosan-based hydrogels with customizable mechanical properties, controllable swelling behavior, and regulated degradation kinetics. Importantly, cell-laden iCsgel demonstrated excellent cytocompatibility and supported cell proliferation. As a proof-of-concept, some oligomers were partially modified with a fluorescent dye before the cross-linking process, resulting in decorated iCsgel. In summary, the established injectable oligomer-cross-linked chitosan hydrogels represent a promising platform with tunable material properties, making them well-suited for applications in tissue engineering and various biomedical fields, including bioprinting.

Tissue engineering represents a central strategy in regenerative medicine to restore damaged or missing tissue through structural and functional replacement. In this study, a two-component bioink platform was developed based on amine-anhydride conjugation as a mild crosslinking reaction between synthetic anhydride-containing oligomers (oSMoMA-x) and natural biopolymers. The compatibility of the oligomers with different amine-containing biopolymers, including chitosan, gelatin, and hydrolyzed collagen peptides, was systematically evaluated. To improve cytocompatibility and enable controlled network formation, oSMoMA oligomers with varying anhydride contents were synthesized and characterized, allowing targeted tuning of material properties through comonomer composition. The resulting hydrogels were comparatively assessed with respect to their rheological and physicochemical properties. While hydrogel formation was achieved with all investigated biopolymers, gelatin-based systems exhibited the most favorable characteristics for bioink development. Two gelatin/oSMoMA bioink formulations with distinct gelation behavior were obtained by employing different base catalysts, enabling control over crosslinking kinetics and material properties. Cytocompatibility was comprehensively evaluated using viability assays, demonstrating enhanced metabolic activity of cells encapsulated in gelatin/oSMoMA-3.5 hydrogels compared to established reference systems, with sustained compatibility for up to seven days. Extrusion-based 3D bioprinting was performed using a modified printhead with integrated temperature control to maintain physiological conditions. The bioinks were successfully printed with embedded murine 3T3 fibroblasts, and post-printing analyses confirmed cell proliferation within the hydrogel constructs. Overall, the results demonstrate the broad compatibility of amin-anhydride-crosslinked oSMoMA systems with different biopolymers and highlight gelatin/oSMoMA bioinks as promising cytocompatible materials for stable 3D bioprinting applications in tissue engineering.

The analysis of serum for biomarkers is a standard method in clinical diagnosis and health assessment. The application of Raman spectroscopy to probe biomarkers in serum is increasingly investigated due to its time- and cost-efficiency. However, time-consuming sample preparation is often required to analyze the serum samples. Additionally, hemolyzed samples are commonly discarded due to interference in the measurements. This study focuses on the application of the online coupling of size exclusion chromatography (SEC) to diode array detector (DAD) and capillary-enhanced Raman spectroscopy (CERS) for direct analysis of hemolyzed serum samples. We demonstrate that different protein classes such as serum albumin and immunoglobulin G (IgG) can be identified in hemolyzed serum according to a calculated hit quality index (HQI). Additionally, different oxidation and binding states of the heme prosthetic group are investigated at 532-nm excitation. The online coupling of SEC-DAD-CERS enables the detailed characterization of blood serum proteins, including the differentiation of IgG, serum albumin, and hemoglobin.

Innovative hyphenated technologies, such as size exclusion chromatography coupled with capillary-enhanced Raman spectroscopy (SEC-CERS), enable more comprehensive analyses of biopharmaceutical drug products. However, specialized software for processing and analyzing data from these advanced techniques is often lacking. This study introduces the R package StreamFind, which is designed to help users seamlessly process both chromatographic and Raman spectroscopic data within an integrated workflow. We detail the implementation and structure of StreamFind and demonstrate its ability in the in-depth analysis of biopharmaceutical products. The study shows its capability to differentiate monoclonal antibodies and entire biopharmaceutical formulations and to quantify various components based on their Raman spectra. Principal component analysis (PCA) identified significant differences among the biopharmaceutical products analyzed, while multivariate curve resolution-alternating least squares (MCR-ALS) proved to be an effective method for quantifying different components within these products. The StreamFind platform is designed to be extensible, to facilitate contributions from new users and to support the future integration of additional algorithms to process different types of complex analytical data.

Gelatin-based microparticles have received growing attention as versatile biomaterials over the years. In this study, we investigated the fabrication process of gelatin microparticles with an emulsifier-free water-in-oil technique using design of experiments (DoE). We executed three DoEs for two different gelatin types (type A and type B). We demonstrated that stirring speed is the most significant factor affecting shape parameters of sphericity of particles derived from both gelatin types. An effect of process temperature was only significant for gelatin type A particles. Water-to-oil phase volume ratio was only investigated for type B gelatin and found to impact particle sphericity of microparticles. We also showed a correlation between particle size distribution and shape factors, where an inferior particle shape quality was associated with finer particles. Through 21 verification batches at constant factor settings, we demonstrated high process performance for microparticles (gelatin type B). Overall, we demonstrated effective control in particle size distribution and particle shape factors for both gelatin types. The fabricated gelatin microparticles will subsequently be chemically crosslinked and the achieved control of particle sphericity will be beneficial for the quality of the crosslinked particles.

Due to an aging society and the associated increase in age-related eye diseases of the posterior segment of the eye, an optimized in vitro vitreous model would be beneficial to assess drug release and distribution in preclinical dosage form development. A key component in such a test system is a compartment simulating the vitreous body. Several hydrogels have been proposed for this purpose. In this work the rheological properties of several vitreous body substitutes based on hyaluronic acid, hypromellose, polyacrylamide, gellan gum in combination with hyaluronic acid, and hyaluronic acid in combination with agar were investigated. By systematically comparing these potential in vitro vitreous body substitutes with porcine vitreous bodies within one study employing a series of rheological characterizations, a direct comparison was achieved, allowing opportunities for optimization to be identified. The main characterization focused on the viscosity and loss factor in the linear viscoelastic region and, for the most promising gels, also on the behavior in frequency sweeps. Additionally, the recovery times, pH values, and osmolalities of the gels were determined. Initially, phosphate-buffered saline, which served as the basis for the hydrogels, was successfully adjusted to match the pH and osmolality of porcine and human vitreous bodies. Gels made from gellan gum-hyaluronic acid and hyaluronic acid-agar proved most promising. These could be adjusted in concentrations of 0.034 % gellan gum & 0.264 % hyaluronic acid or 0.22 % hyaluronic acid & 0.09 % agar to match both the viscosity of the vitreous body and the loss factor in the linear viscoelastic region. Additionally, the pH values, osmolalities, and behavior in frequency sweeps of the gels were also comparable to the vitreous body, as these exhibit physicochemical gel formation mechanisms and reversibly linked frameworks probably similar to those of the vitreous body. Under the measurement conditions used here, the gels can therefore be considered as good in vitro vitreous body substitutes. Further diffusion studies, which will likely be influenced by the adjusted rheological properties, should be conducted in the future to further investigate the suitability of the optimized gels presented here.

Purpose:Hydrogels derived from decellularized tissues are promising biomaterials in tissue engineering, but their rapid biodegradation can hinder in vitro cultivation. This study aimed to retard biodegradation of a hydrogel derived from porcine decellularized lacrimal glands (dLG-HG) by crosslinking with genipin to increase the mechanical stability without affecting the function and viability of lacrimal gland (LG)-associated cells. Methods:The effect of different genipin concentrations on dLG-HG stiffness was measured rheologically. Cell-dependent biodegradation was quantified over 10 days, and the impact on matrix metalloproteinase (MMP) activity was quantified by gelatin and collagen zymography. The viability of LG epithelial cells (EpCs), mesenchymal stem cells (MSCs), and endothelial cells (ECs) cultured on genipin-crosslinked dLG-HG was assessed after 10 days, and EpC secretory activity was analyzed by β-hexosaminidase assay. Results:The 0.5-mM genipin increased the stiffness of dLG-HG by about 46%, and concentrations > 0.25 mM caused delayed cell-dependent biodegradation and reduced MMP activity. The viability of EpCs, MSCs, and ECs was not affected by genipin concentrations of up to 0.5 mM after 10 days. Moreover, up to 0.5-mM genipin did not negatively affect EpC secretory activity compared to control groups. Conclusions:A concentration of 0.5-mM genipin increased dLG-HG stiffness, and 0.25-mM genipin was sufficient to prevent MMP-dependent degradation. Importantly, concentrations of up to 0.5-mM genipin did not compromise the viability of LG-associated cells or the secretory activity of EpCs. Thus, crosslinking with genipin improves the properties of dLG-HG for use as a substrate in LG tissue engineering.

This study presents the effects of treating polystyrene (PS) cell culture plastic with oxidoreductase enzyme laccase and the catechol substrates caffeic acid (CA), L-DOPA, and dopamine on the culturing of normal human epidermal melanocytes (NHEMs) and human embryonal carcinoma cells (NTERA-2). The laccase–substrate treatment improved PS hydrophilicity and roughness, increasing NHEM and NTERA-2 adherence, proliferation, and NHEM melanogenesis to a level comparable with conventional plasma treatment. Cell adherence dynamics and proliferation were evaluated. The NHEM endpoint function was quantified by measuring melanin content. PS surfaces treated with laccase and its substrates demonstrated the forming of polymer-like structures. The surface texture roughness gradient and the peak curvature were higher on PS treated with a combination of laccase and substrates than laccase alone. The number of adherent NHEM and NTERA-2 was significantly higher than on the untreated surface. The proliferation of NHEM and NTERA-2 correspondingly increased on treated surfaces. NHEM melanin content was enhanced 6-10-fold on treated surfaces. In summary, laccase- and laccase–substrate-modified PS possess improved PS surface chemistry/hydrophilicity and altered roughness compared to untreated and plasma-treated surfaces, facilitating cellular adherence, subsequent proliferation, and exertion of the melanotic phenotype. The presented technology is easy to apply and creates a promising custom-made, substrate-based, cell-type-specific platform for both 2D and 3D cell culture.

Sustainable treatment of aqueous deficient dry eye (ADDE) represents an unmet medical need and therefore requires new curative and regenerative approaches based on appropriate in vitro models. Tissue specific hydrogels retain the individual biochemical composition of the extracellular matrix and thus promote the inherent cell ' s physiological function. Hence, we created a decellularized lacrimal gland (LG) hydrogel (dLG-HG) meeting the requirements for a bioink as the basis of a LG model with potential for in vitro ADDE studies. Varying hydrolysis durations were compared to obtain dLG-HG with best possible physical and ultrastructural properties while preserving the original biochemical composition. A particular focus was placed on dLG-HG ' s impact on viability and functionality of LG associated cell types with relevance for a future in vitro model in comparison to the unspecific single component hydrogel collagen type-I (Col) and the common cell culture substrate Matrigel. Proliferation of LG epithelial cells (EpC), LG mesenchymal stem cells, and endothelial cells cultured on dLG-HG was enhanced compared to culture on Matrigel. Most importantly with respect to a functional in vitro model, the secretion capacity of EpC cultured on dLG-HG was higher than that of EpC cultured on Col or Matrigel. In addition to these promising cell related properties, a rapid matrix metalloproteinase-dependent biodegradation was observed, which on the one hand suggests a lively cell-matrix interaction, but on the other hand limits the cultivation period. Concluding, dLG-HG possesses decisive properties for the tissue engineering of a LG in vitro model such as cytocompatibility and promotion of secretion, making it superior to unspecific cell culture substrates. However, deceleration of biodegradation should be addressed in future experiments.

In this study, deep UV resonance Raman spectroscopy (DUV-RRS) was coupled with high performance liquid chromatography (HPLC) to be applied in the field of pharmaceutical analysis. Naproxen, Metformin and Epirubicin were employed as active pharmaceutical ingredients (APIs) covering different areas of the pharmacological spectrum. Raman signals were successfully generated and attributed to the test substances, even in the presence of the dominant solvent bands of the mobile phase. To increase sensitivity, a low-flow method was developed to extend the exposure time of the sample. This approach enabled the use of a deep UV pulse laser with a low average power of 0.5 mW. Compared to previous studies, where energy-intensive argon ion lasers were commonly used, we were able to achieve similar detection limits with our setup. Using affordable lasers with low operating costs may facilitate the transfer of the results of this study into practical applications.

This study describes the synthesis, radiofluorination and purification of an anionic amphiphilic teroligomer developed as a stabilizer for siRNA-loaded calcium phosphate nanoparticles (CaP-NPs). As the stabilizing amphiphile accumulates on nanoparticle surfaces, the fluorine-18-labeled polymer should enable to track the distribution of the CaP-NPs in brain tumors by positron emission tomography after application by convection-enhanced delivery. At first, an unmodified teroligomer was synthesized with a number average molecular weight of 4550 ± 20 Da by free radical polymerization of a defined composition of methoxy-PEG-monomethacrylate, tetradecyl acrylate and maleic anhydride. Subsequent derivatization of anhydrides with azido-TEG-amine provided an azido-functionalized polymer precursor (o14PEGMA-N3) for radiofluorination. The 18F-labeling was accomplished through the copper-catalyzed cycloaddition of o14PEGMA-N3 with diethylene glycol–alkyne-substituted heteroaromatic prosthetic group [18F]2, which was synthesized with a radiochemical yield (RCY) of about 38% within 60 min using a radiosynthesis module. The 18F-labeled polymer [18F]fluoro-o14PEGMA was obtained after a short reaction time of 2–3 min by using CuSO4/sodium ascorbate at 90 °C. Purification was performed by solid-phase extraction on an anion-exchange cartridge followed by size-exclusion chromatography to obtain [18F]fluoro-o14PEGMA with a high radiochemical purity and an RCY of about 15%.

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.

The online coupling of size exclusion chromatography (SEC) to capillary enhanced Raman spectroscopy (CERS) based on a liquid core waveguide (LCW) flow cell was applied for the first time to assess the higher-order structure of different proteins. This setup allows recording of Raman spectra of the monomeric protein within complex mixtures, since SEC enables the separation of the monomeric protein from matrix components such as excipients of a biopharmaceutical product and higher molecular weight species (e.g., aggregates). The acquired Raman spectra were used for structural elucidation of well characterized proteins such as bovine serum albumin, hen egg white lysozyme, and β-lactoglobulin and of the monoclonal antibody rituximab in a medicinal product. Additionally, the CERS detection of the disaccharide sucrose, which is used as a stabilizing excipient, was quantified to achieve a limit of detection (LOD) of 120 μg and a limit of quantification (LOQ) of 363 μg injected on the column.

A three-dimensional (3D) scaffold ideally provides hierarchical complexity and imitates the chemistry and mechanical properties of the natural cell environment. Here, we report on a stimuli-responsive photo-cross-linkable resin formulation for the fabrication of scaffolds by continuous digital light processing (cDLP), which allows for the mechano-stimulation of adherent cells. The resin comprises a network-forming trifunctional acrylate ester monomer (trimethylolpropane triacrylate, or TMPTA), N-isopropyl acrylamide (NiPAAm), cationic dimethylaminoethyl acrylate (DMAEA) for enhanced cell interaction, and 4-acryloyl morpholine (AMO) to adjust the phase transition temperature (Ttrans) of the equilibrium swollen cross-polymerized scaffold. With glycofurol as a biocompatible solvent, controlled three-dimensional structures were fabricated and the transition temperatures were adjusted by resin composition. The effects of the thermally induced mechano-stimulation were investigated with mouse fibroblasts (L929) and myoblasts (C2C12) on printed constructs. Periodic changes in the culture temperature stimulated the myoblast proliferation.