Bone fractures are most often seen in racetrack horses because of the high level of intensity in racing. These issues are the main cause of decreased performance in racehorses. Mesenchymal stem cells (MSCs) have been explored to improve intra-articular therapy in racehorses. MSCs are essential for the repair and regeneration of damaged tissues. In this study, the effect of intra-articular injection of MSCs in racehorses was investigated. Before accessing the MSC therapy, synovial fluids were obtained from the fracture site of racehorses, and adipose tissue was collected for MSC isolation. Using the MSC specific marker, adipose tissue-derived MSCs were identified. The racehorses received intra-articular injection of autologous MSCs (or allogeneic) (3 × 107 cells/3 mL). After 1 or 2 weeks, synovial fluids were collected from racehorses. To test the effect of MSC injection using ELISA, we analyzed inflammatory factors from the untreated samples compared to MSC-treated samples of racehorses. The level of pro-inflammatory factors (interleukin-1β and prostaglandin E2) was significantly decreased in synovial fluids of MSC-injected racehorses, compared to before accessing the MSC therapy, whereas, the level of anti-inflammatory factor (interleukin-10) was higher than prior to accessing the MSC therapy. Further studies are needed to investigate the anti-inflammatory mechanism of MSC in racehorses.

The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.