Tendon-derived extracellular matrix induces mesenchymal stem cell tenogenesis via an integrin/transforming growth factor-ß crosstalk-mediated mechanism.

Treatment of tendon injuries is challenging. To develop means to augment tendon regeneration, we have previously prepared a soluble, low immunogenic (DNA-free), tendon extracellular matrix fraction (tECM) by urea extraction of juvenile bovine tendons, which is capable of enhancing transforming growth factor-ß (TGF-ß) mediated tenogenesis in human adipose-derived stem cells (hASCs). Here, we aimed to elucidate the mechanism of tECM-driven hASC tenogenic differentiation in vitro, focusing on the integrin and TGF-ß/SMAD pathways. Our results showed that tECM promoted hASC proliferation and tenogenic differentiation in vitro based on tenogenesis-associated markers. tECM also induced higher expression of several integrin subunits and TGF-ß receptors, and nuclear translocation of p-SMAD2 in hASCs. Pharmacological inhibition of integrin-ECM binding, focal adhesion kinase (FAK) signaling, or TGF-ß signaling independently led to compromised pro-tenogenic effects of tECM and actin fiber polymerization. Additionally, integrin blockade inhibited tECM-driven TGFBR2 expression, while inhibiting TGF-ß signaling decreased tECM-mediated expression of integrin α1, α2, and ß1 in hASCs. Together, these findings suggest that the strong pro-tenogenic bioactivity of tECM is regulated via integrin/TGF-ß signaling crosstalk. Understanding how integrins interact with signaling by TGF-ß and/or other growth factors (GFs) within the tendon ECM microenvironment will provide a rational basis for an ECM-based approach for tendon repair.

Prediction of Total Knee Arthroplasty Sizes with Demographics, including Hand and Foot Sizes.

Anticipating implant sizes before total knee arthroplasty (TKA) allows the surgical team to streamline operations and prepare for potential difficulties. This study aims to determine the correlation and derive a regression model for predicting TKA sizes using patient-specific demographics without using radiographs. We reviewed the demographics, including hand and foot sizes, of 1,339 primary TKAs. To allow for comparison across different TKA designs, we converted the femur and tibia sizes into their anteroposterior (AP) and mediolateral (ML) dimensions. Stepwise multivariate regressions were performed to analyze the data. Regarding the femur component, the patient's foot, gender, height, hand circumference, body mass index, and age was the significant demographic factors in the regression analysis (R-square 0.541, p < 0.05). For the tibia component, the significant factors in the regression analysis were the patient's foot size, gender, height, hand circumference, and age (R-square 0.608, p < 0.05). The patient's foot size had the highest correlation coefficient for both femur (0.670) and tibia (0.697) implant sizes (p < 0.05). We accurately predicted the femur component size exactly, within one and two sizes in 49.5, 94.2, and 99.9% of cases, respectively. Regarding the tibia, the prediction was exact, within one and two sizes in 53.0, 96.0, and 100% of cases, respectively. The regression model, utilizing patient-specific characteristics, such as foot size and hand circumference, accurately predicted TKA femur and tibia sizes within one component size. This provides a more efficient alternative for preoperative planning.