Melanie Lynn Hart

Incorporating nanofibers into 3D‐printed scaffolds is an effective strategy to enhance the physicochemical properties and osteogenic bioactivity of bone tissue engineering constructs. In this study, we developed a composite scaffold featuring a dual‐nanofiber interpenetrating network composed of silica (SiO ₂ ) and poly(L‐lactic acid)/gelatin (PLLA/GEL) nanofibers. SiO ₂ nanofibers were employed to reinforce mechanical properties and release bioactive Si elements, establishing a favorable osteogenic microenvironment. Concurrently, PLLA/GEL nanofibers were chemically crosslinked with the sodium alginate (SA) matrix to stabilize the scaffold structure. This design effectively addresses the structural instability often observed in single‐component inorganic fiber systems. Notably, systematic comparative experiments clarified the distinct contributions of each component. Results indicated that PLLA/GEL nanofibers primarily contributed to mechanical stability; however, their osteogenic contribution was not significantly superior to PLLA particles. In contrast, SiO ₂ nanofibers exhibited superior bioactivity compared to nanoparticles in inducing osteogenic differentiation and promoting pro‐reparative macrophage polarization, leading to enhanced in vivo bone repair. This dual‐nanofiber network complementarily improves mechanical stability, modulates inflammation, and promotes osteogenic efficacy, offering a novel strategy for designing high‐performance functional bone tissue engineering scaffolds.

Degenerative disc disease remains a primary cause of chronic back pain, yet current surgical treatments are often limited by the mechanical mismatch between implants and native intervertebral disc (IVD) tissue. This study investigates additively manufactured functionally graded Gyroid structures based on thermoplastic polyurethane (TPU) as biomimetic IVD replacements, focusing on the influence of geometry and material gradients on mechanical performance. Gyroid-based constructs were fabricated by multi-material fused filament fabrication using TPU filaments of different stiffness. Their mechanical performance was evaluated under static and dynamic compressive loading. Finite element analysis was performed to investigate stress distribution within the Gyroid architecture, while micro-computed tomography (µCT) was used to assess manufacturing-related defects and structural integrity before and after 700 000 loading cycles. All investigated structures exhibited stable and reproducible mechanical behavior. However, only a single geometric configuration reached the targeted physiological load range of 4000–8000 N, irrespective of the material combination. The incorporation of an additional compliant TPU phase did not significantly alter the global force–deformation response compared with two-material configurations, indicating that structural geometry predominantly governs the compressive mechanical behavior. Dynamic testing demonstrated consistent damping capacities of approximately 20% across all configurations together with stable stiffness, storage modulus, and loss modulus during fatigue loading. Finite element analysis revealed homogeneous load distribution with localized stress concentrations at the curved Gyroid junctions. Quantitative µCT analysis showed no measurable increase in micro-porosity, void fraction, or interfacial defects after 600 000 loading cycles. The findings demonstrate that the mechanical performance of TPU-based Gyroid IVD constructs is primarily governed by architectural design rather than material gradients under compressive loading. The combined experimental, numerical, and µCT analyses confirm the mechanical robustness and structural stability of the proposed functionally graded Gyroid structures, highlighting architecture-driven design as a promising strategy for mechanically compatible IVD replacements.

Introduction: Ex vivo swelling and curling can undermine reproducibility in compression-based injury models. Methods: We developed a simple, regression-guided flattening step that computes explant-specific loads from each explant’s swelling state to restore native thickness and flatness prior to loading. Using adult articular cartilage, we tested the hypothesis that mitigating initial deformation amplifies injury model readouts and permits standardized injury of the deformation-prone superficial zone (SZ), which many models exclude. Results: Discs spanning 250–1200 µm exhibited curling; 250 µm SZ discs were chosen for calibration. Post-equilibration thickness (T ₂ ) strongly predicted the load required to restore native thickness (LT ₀ ), and nonlinear regression yielded a practical load-prediction equation, refined with an expanded dataset (n = 129 discs). Applying the predicted flattening load immediately before standardized compression (50%–65% strain, 100%·s ^-1 ) did not affect chondrocyte viability on its own. When combined with injury, it amplified canonical readouts - lower viability and higher apoptosis - with effects concentrated in the upper superficial zone, notably within the top 44 μm at 24 h and with apoptosis persisting to 96 h. Click-chemistry EdU labeling revealed injury-induced proliferation: SZ-wide S-phase entry, most pronounced at 96 h in adult, mechanically mature cartilage without exogenous growth factors. Discussion: Together, regression-guided flattening restores native geometry, standardizes the mechanical stimulus, increases readout reliability, and enables inclusion of the clinically important SZ. Because deformation artifacts are common across hydrated soft tissues, and prior pre-compression practices were uncalibrated, this framework establishes a cartilage-based proof of concept for regression-guided flattening that may be extendable to other deformation-prone tissues through tissue-specific recalibration and experimental validation, thereby providing a more standardized and generalizable route to faithful ex vivo injury studies.

Cell micro-patterning controls cell fate and function and has potential for generating therapeutically usable mesenchymal stromal cell (MSC) populations with precise functions. However, to date, the micro-patterning of human cells in a translational context has been impossible because only ruminant media supplements, e.g. fetal bovine serum (FBS), are established for use with micro-patterns (MPs). Thus, there are currently no good manufacturing practice (GMP)-compliant media available for MPs. This study tested a xenogenic-free human plasma and platelet lysate (hP + PL) medium supplement to determine its compatibility with MPs. Unfiltered hP + PL medium resulted in significant protein deposition, creating a ‘carpet-like’ layer that rendered MPs ineffective. Filtration (3×/5×) eliminated this effect. Importantly, quantitative comparison using droplet digital PCR revealed that human MSCs in all media types exhibited similar profiles with strong myogenic Calponin 1/Transgelin 2 (TAGLN2) and weaker osteogenic alkaline phosphatase/Runt-related transcription factor 2 marker expression, and much weaker adipogenic (lipoprotein lipase/peroxisome proliferator-activated receptor gamma) and chondrogenic (collagen type II/aggrecan) expression, with profiles being dominated by myogenic markers. Within these similar profiles, an even stronger induction of the myogenic marker TAGLN2 by all hP + PL- compared to FBS-containing media. Overall, this suggested that FBS can be replaced with hP + PL without altering differentiation profiles. However, assessing individual MSC responses to various MP types with defined categories revealed that unfiltered hP + PL medium was unusable. Importantly, FBS- and 3× filtered hP + PL media were comparable in each differentiation category. Summarized, this study recommends 3× filtered hP + PL as a xenogenic-free and potentially GMP-compliant alternative to FBS as a culture medium supplement for micro-patterning cell populations in both basic and translational research that will ensure consistent and reliable MSC micro-patterning for therapeutic use.

Micropatterns (MPs) are widely used as a powerful tool to control cell morphology and phenotype. However, methods for determining the effectiveness of how well cells are controlled by the shape of MPs have been inconsistently used and studies rarely report on this topic, indicating lack of standardization. We introduce an evaluation score that quantitatively assesses the MP fabrication quality and effectiveness, which can be broadly used in conjunction with all currently available MP design types. This score uses four simple and quick steps: (i) scoring MP and (ii) background fabrication quality, (iii) defining the type(s) of MP of interest, and (iv) assigning so-called efficiency descriptors describing cell behavior. These steps are based on visual inspection and quick categorization of various aspects of MP fabrication quality and cell behaviour, presented in illustrations and microscopy image examples intended to serve as a reference "atlas". To illustrate the advantage of using this score, we determined differences in cell morphology and F-actin intensity between scored vs. non-scored cells. These measurements, which could be different in other studies, were chosen because both are understood as markers of cell phenotype and function. We combined intensity-calibrated immunofluorescence microscopy and image-based single cell protein analysis. Importantly, significant differences in cell morphology and cytoskeletal protein content between scored vs. non-scored cells were noted: the unconditional inclusion of all experimental read-outs (i.e., all MP data regardless of MP quality and effectiveness) into the final results significantly misjudged the experimental readouts vs. only including experimental read-outs of quality-controlled and effective MPs, identified by scoring. Specifically, non-scoring underestimated the F-actin intensity per cell and quantitative cellular morphometric descriptors circularity and solidity and overestimated aspect ratio. Scoring improved the precision of cellular readouts, advocating the use of a MP quality and efficiency score as a quantitative decision-supporting tool in deciding whether or not particular MPs should be used for experiments, saving time and money. This simple scoring methodology can be used for improving MP fabrication, comparing results across studies, benefiting basic science studies and potential future clinical use of MPs by introducing standardization.

Introduction: The last decade has led to rapid developments and increased usage of computational tools at the single-cell level. However, our knowledge remains limited in how extracellular cues alter quantitative macrophage morphology and how such morphological changes can be used to predict macrophage phenotype as well as cytokine content at the single-cell level.Methods: Using an artificial intelligence (AI) based approach, this study determined whether (i) accurate macrophage classification and (ii) prediction of intracellular IL-10 at the single-cell level was possible, using only morphological features as predictors for AI. Using a quantitative panel of shape descriptors, our study assessed image-based original and synthetic single-cell data in two different datasets in which CD14+ monocyte-derived macrophages generated from human peripheral blood monocytes were initially primed with GM-CSF or M-CSF followed by polarization with specific stimuli in the presence/absence of continuous GM-CSF or M-CSF. Specifically, M0, M1 (GM-CSF-M1, TNFα/IFNγ-M1, GM-CSF/TNFα/IFNγ-M1) and M2 (M-CSF-M2, IL-4-M2a, M-CSF/IL-4-M2a, IL-10-M2c, M-CSF/IL-10-M2c) macrophages were examined.Results: Phenotypes were confirmed by ELISA and immunostaining of CD markers. Variations of polarization techniques significantly changed multiple macrophage morphological features, demonstrating that macrophage morphology is a highly sensitive, dynamic marker of phenotype. Using original and synthetic single-cell data, cell morphology alone yielded an accuracy of 93% for the classification of 6 different human macrophage phenotypes (with continuous GM-CSF or M-CSF). A similarly high phenotype classification accuracy of 95% was reached with data generated with different stimuli (discontinuous GM-CSF or M-CSF) and measured at a different time point. These comparably high accuracies clearly validated the here chosen AI-based approach. Quantitative morphology also allowed prediction of intracellular IL-10 with 95% accuracy using only original data.Discussion: Thus, image-based machine learning using morphology-based features not only (i) classified M0, M1 and M2 macrophages but also (ii) classified M2a and M2c subtypes and (iii) predicted intracellular IL-10 at the single-cell level among six phenotypes. This simple approach can be used as a general strategy not only for macrophage phenotyping but also for prediction of IL-10 content of any IL-10 producing cell, which can help improve our understanding of cytokine biology at the single-cell level.

Background: The treatment of grafts with vancomycin for ligament reconstruction in knee surgery is the current standard. However, high antibiotic concentrations have chondrotoxic effects. Purpose: To test the chondrotoxicity of clindamycin, gentamicin and vancomycin in comparable concentrations. In vitro and in vivo effective concentrations hugely vary from drug to drug. To allow for comparisons between these three commonly used antibiotics, the concentration ranges frequently used in orthopedic surgical settings were tested. Study Design: Controlled laboratory study. Methods: Human cartilage from 10 specimens was used to isolate chondrocytes. The chondrocytes were treated with clindamycin (1 mg/mL and 0.5 mg/mL), gentamicin (10 mg/mL and 5 mg/mL) or vancomycin (10 mg/mL and 5 mg/mL), at concentrations used for preoperative infection prophylaxis in ligament surgery. Observations were taken over a period of 7 days. A control of untreated chondrocytes was included. To test the chondrotoxicity, a lactate dehydrogenase (LDH) test and a water-soluble tetrazolium salt (WST-1) assay were performed on days 1, 3 and 7. In addition, microscopic examinations were performed after fluorescence staining of the cells at the same time intervals. Results: All samples showed a reasonable vitality of the cartilage cells after 72 h. However, clindamycin and gentamicin both showed higher chondrotoxicity in all investigations compared to vancomycin. After a period of 7 days, only chondrocytes treated with vancomycin showed reasonable vitality. Conclusions: The preoperative treatment of ligament grafts with vancomycin is the most reasonable method for infection prophylaxis, in accordance with the current study results regarding chondrotoxicity; however, clindamycin and gentamicin cover a wider anti-bacterial spectrum. Clinical Relevance: The prophylactic antibiotic treatment of ligament grafts at concentrations of 5 mg/mL or 10 mg/mL vancomycin is justifiable and reasonable. In specific cases, even the use of gentamicin and clindamycin is appropriate.

This review presents the changes that the imaging of articular cartilage has undergone throughout the last decades. It highlights that the expectation is no longer to image the structure and associated functions of articular cartilage but, instead, to devise methods for generating non-invasive, function-depicting images with quantitative information that is useful for detecting the early, pre-clinical stage of diseases such as primary or post-traumatic osteoarthritis (OA/PTOA). In this context, this review summarizes (a) the structure and function of articular cartilage as a molecular imaging target, (b) quantitative MRI for non-invasive assessment of articular cartilage composition, microstructure, and function with the current state of medical diagnostic imaging, (c), non-destructive imaging methods, (c) non-destructive quantitative articular cartilage live-imaging methods, (d) artificial intelligence (AI) classification of degeneration and prediction of OA progression, and (e) our contribution to this field, which is an AI-supported, non-destructive quantitative optical biopsy for early disease detection that operates on a digital tissue architectural fingerprint. Collectively, this review shows that articular cartilage imaging has undergone profound changes in the purpose and expectations for which cartilage imaging is used; the image is becoming an AI-usable biomarker with non-invasive quantitative functional information. This may aid in the development of translational diagnostic applications and preventive or early therapeutic interventions that are yet beyond our reach.

Despite lignin’s global abundance and its use in biomedical studies, our understanding of how lignin regulates disease through modulation of cell morphology and associated phenotype of human cells is unknown. We combined an automated high-throughput image cell segmentation technique for quantitatively measuring a panel of cell shape descriptors, droplet digital Polymerase Chain Reaction for absolute quantification of gene expression and multivariate data analyses to determine whether lignin could therapeutically modulate the cell morphology and phenotype of inflamed, degenerating diseased human cells (osteoarthritic (OA) chondrocytes) towards a healthier cell morphology and phenotype. Lignin dose-dependently modified all aspects of cell morphology and ameliorated the diseased shape of OA chondrocytes by inducing a less fibroblastic healthier cell shape, which correlated with the downregulation of collagen 1A2 (COL1A2, a major fibrosis-inducing gene), upregulation of collagen 2A1 (COL2A1, a healthy extracellular matrix-inducing gene) and downregulation of interleukin-6 (IL-6, a chronic inflammatory cytokine). This is the first study to show that lignin can therapeutically target cell morphology and change a diseased cells’ function towards a healthier cell shape and phenotype. This opens up novel opportunities for exploiting lignin in modulation of disease, tissue degeneration, fibrosis, inflammation and regenerative medical implants for therapeutically targeting cell function and outcome.