Multimodality scoring of chondral injuries in the equine fetlock joint ex vivo

Autologous iPSC- and MSC-derived chondrocyte implants for cartilage repair in a miniature pig model

BACKGROUND

Induced pluripotent stem cell (iPSC)-derived mesenchymal stem cells (iMSCs) have greater potential for generating chondrocytes without hypertrophic and fibrotic phenotypes compared to bone marrow-derived mesenchymal stem/stromal cells (BMSCs). However, there is a lack of research demonstrating the use of autologous iMSCs for repairing articular chondral lesions in large animal models. In this study, we aimed to evaluate the effectiveness of autologous miniature pig (minipig) iMSC-chondrocyte (iMSC-Ch)-laden implants in comparison to autologous BMSC-chondrocyte (BMSC-Ch)-laden implants for cartilage repair in porcine femoral condyles.

METHODS

iMSCs and BMSCs were seeded into fibrin glue/nanofiber constructs and cultured with chondrogenic induction media for 7 days before implantation. To assess the regenerative capacity of the cells, 19 skeletally mature Yucatan minipigs were randomly divided into microfracture control, acellular scaffold, iMSC, and BMSC subgroups. A cylindrical defect measuring 7 mm in diameter and 0.6 mm in depth was created on the articular cartilage surface without violating the subchondral bone. The defects were then left untreated or treated with acellular or cellular implants.

RESULTS

Both cellular implant-treated groups exhibited enhanced joint repair compared to the microfracture and acellular control groups. Immunofluorescence analysis yielded significant findings, showing that cartilage treated with iMSC-Ch implants exhibited higher expression of COL2A1 and minimal to no expression of COL1A1 and COL10A1, in contrast to the BMSC-Ch-treated group. This indicates that the iMSC-Ch implants generated more hyaline cartilage-like tissue compared to the BMSC-Ch implants.

CONCLUSIONS

Our findings contribute to filling the knowledge gap regarding the use of autologous iPSC derivatives for cartilage repair in a translational animal model. Moreover, these results highlight their potential as a safe and effective therapeutic strategy.

Characterization of connective tissues using near-infrared spectroscopy and imaging

Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue's biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.

Combination of optical coherence tomography and near infrared spectroscopy enhances determination of articular cartilage composition and structure

Conventional arthroscopic evaluation of articular cartilage is subjective and poorly reproducible. Therefore, implementation of quantitative diagnostic techniques, such as near infrared spectroscopy (NIRS) and optical coherence tomography (OCT), is essential. Locations (n = 44) with various cartilage conditions were selected from mature equine fetlock joints (n = 5). These locations and their surroundings were measured with NIRS and OCT (n = 530). As a reference, cartilage proteoglycan (PG) and collagen contents, and collagen network organization were determined using quantitative microscopy. Additionally, lesion severity visualized in OCT images was graded with an automatic algorithm according to International Cartilage Research Society (ICRS) scoring system. Artificial neural network with variable selection was then employed to predict cartilage composition in the superficial and deep zones from NIRS data, and the performance of two models, generalized (including all samples) and condition-specific models (based on ICRS-grades), was compared. Spectral data correlated significantly (p < 0.002) with PG and collagen contents, and collagen orientation in the superficial and deep zones. The combination of NIRS and OCT provided the most reliable outcome, with condition-specific models having lower prediction errors (9.2%) compared to generalized models (10.4%). Therefore, the results highlight the potential of combining both modalities for comprehensive evaluation of cartilage during arthroscopy.