Sarcopenia refers to a decline in muscle mass and strength with age, causing significant impairment in the ability to carry out normal daily functions and increased risk of falls and fractures, eventually leading to loss of independence. Maintaining protein homeostasis is an important factor in preventing muscle loss, and the decrease in muscle mass is caused by an imbalance between anabolism and catabolism of muscle proteins. Although β-sitosterol has various effects such as anti-inflammatory, protective effect against nonalcoholic fatty liver disease (NAFLD), antioxidant, and antidiabetic activity, the mechanism of β-sitosterol effect on the catabolic pathway was not well known. β-sitosterol was assessed in vitro and in vivo using a dexamethasone-induced muscle atrophy mice model and C2C12 myoblasts. β-sitosterol protected mice from dexamethasone-induced muscle mass loss. The thickness of gastrocnemius muscle myofibers was increased in dexamethasone with the β-sitosterol treatment group (DS). Grip strength and creatine kinase (CK) activity were also recovered when β-sitosterol was treated. The muscle loss inhibitory efficacy of β-sitosterol in dexamethasone-induced muscle atrophy in C2C12 myotube was also verified in C2C12 myoblast. β-sitosterol also recovered the width of myotubes. The protein expression of muscle atrophy F-box (MAFbx) was increased in dexamethasone-treated animal models and C2C12 myoblast, but it was reduced when β-sitosterol was treated. MuRF1 also showed similar results to MAFbx in the mRNA level of C2C12 myotubes. In addition, in the gastrocnemius and tibialis anterior muscles of mouse models, Forkhead Box O1 (FoxO1) protein was increased in the dexamethasone-treated group (Dexa) compared with the control group and reduced in the DS group. Therefore, β-sitosterol would be a potential treatment agent for aging sarcopenia.

One of the causes of sarcopenia is that homeostasis between anabolism and catabolism breaks down due to muscle metabolism changes. Rutin has shown antioxidant and anti-inflammatory effects in various diseases, but there are few studies on the effect on muscle loss with aging. The effect of rutin on muscle loss was evaluated using dexamethasone-induced muscle loss C2C12 myoblast and mouse model. In the group treated with dexamethasone, the muscle weight of gastrocnemius (GA), tibialis anterior (TA), and extensor digitorum longus (EDL) in the mouse model were significantly decreased (p < 0.0001 in GA, p < 0.0001 in TA, and p < 0.001 in EDL) but recovered (p < 0.01 in GA, p < 0.0001 in TA, and p < 0.01 in EDL) when treated with rutin. MAFbx, MuRF1, and FOXO3 protein expression of C2C12 myoblast were significantly increased (p < 0.01 in MAFbx, p < 0.01 in MuRF1, and p < 0.01 in FOXO3) when treated with dexamethasone, but it was recovered (p < 0.01 in MAFbx, p < 0.01 in MuRF1, and p < 0.01 in FOXO3) when rutin was treated. In addition, MAFbx and FOXO3 protein expression in GA of mouse model was significantly increased (p < 0.0001 in MAFbx and p < 0.001 in FOXO3) when treated with dexamethasone, but it was also recovered (p < 0.01 in MAFbx and p < 0.001 in FOXO3) when rutin was treated. The present study shows that rutin blocks the FOXO3/MAFbx and FOXO3/MuRf1 pathways to prevent protein catabolism. Therefore, rutin could be a potential agent for muscle loss such as sarcopenia through the blocking ubiquitin-proteasome pathway associated with catabolic protein degradation.

Previous studies have shown that mesenchymal stem cells (MSCs) derived from various tissue sources can be differentiated into smooth muscle‐like cells (SMLCs) in vitro. In this paper, dental pulp‐derived mesenchymal stem cells (DPSCs) were evaluated for their differentiation ability towards smooth muscle‐like cells (SMLCs) under the effect of widely used cytokines (TGF‐β1 and PDGF‐BB) with special focus on different culturing environments. For this purpose, both the commercially used culturing plates (Norm‐c) and 0.1% gelatin‐precoated (Gel‐c) plates were used. Isolated cells displayed plastic adherence, pluripotency and cell surface marker profiling, and adipogenic and osteogenic differentiation potential with lineage specific marker expression. Differentiated cells induced under different culturing plates showed successful differentiation into SMLCs by positively expressing smooth muscle cell (SMC) specific markers both at the mRNA and protein levels. Gelatin coating could substantially enhance DPSC differentiation potential than Norm‐c‐induced cells. However, the absence of mature marker MHY‐11 by immunostaining results from all treatment groups further indicated the development of immature and synthetic SMLCs. Finally, it was concluded that DPSC differentiation ability into SMLCs can be enhanced under cytokine treatment as well as by altering the cellular niche by precoating the culturing plates with suitable substrates. However, to get fully functional, contractile, and mature SMLCs, still many different cytokine cocktail combinations and more suitable coating substrates will be needed.

Background: Dual energy X-ray absorptiometry (DXA) is a preferred modality for screening or diagnosis of osteoporosis and can predict the risk of hip fracture. However, the DXA test is difficult to implement easily in some developing countries, and fractures have been observed before patients underwent DXA. The purpose of this systematic review is to search for studies that predict the risk of hip fracture using artificial intelligence (AI) or machine learning, organize the results of each study, and analyze the usefulness of this technology.Methods: The PubMed, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched including “hip fractures” AND “artificial intelligence”.Results: A total of 7 studies are included in this study. The total number of subjects included in the 7 studies was 330,099. There were 3 studies that included only women, and 4 studies included both men and women. One study conducted AI training after 1:1 matching between fractured and non-fractured patients. The area under the curve of AI prediction model for hip fracture risk was 0.39 to 0.96. The accuracy of AI prediction model for hip fracture risk was 70.26% to 90%.Conclusions: We believe that predicting the risk of hip fracture by the AI model will help select patients with high fracture risk among osteoporosis patients. However, to apply the AI model to the prediction of hip fracture risk in clinical situations, it is necessary to identify the characteristics of the dataset and AI model and use it after performing appropriate validation.

Lee SY, et al. Clin Orthop Surg. 2023 Feb;15:e13. https://doi.org/10.4055/cios22280

One of the most severe and devastating cancer is pancreatic cancer. Pancreatic ductal adenocarcinoma (PDAC) is one of the major pancreatic exocrine cancer with a poor prognosis and growing prevalence. It is the most deadly disease, with an overall five-year survival rate of 6% to 10%. According to various reports, it has been demonstrated that pancreatic cancer stem cells (PCSCs) are the main factor responsible for the tumor development, proliferation, resistance to anti-cancer drugs, and recurrence of tumors after surgery. PCSCs have encouraged new therapeutic methods to be explored that can specifically target cancer cells. Furthermore, stem cells, especially mesenchymal stem cells (MSCs), are known as influential anti-cancer agents as they function through anti-inflammatory, paracrine, cytokines, and chemokine′s action. The properties of MSCs, such as migration to the site of infection and host immune cell activation by its secretome, seem to control the microenvironment of the pancreatic tumor. MSCs secretome exhibits similar therapeutic advantages as a conventional cell-based therapy. Moreover, the potential for drug delivery could be enhanced by engineered MSCs to increase drug bioactivity and absorption at the tumor site. In this review, we have discussed available therapeutic strategies, treatment hurdles, and the role of different factors such as PCSCs, cysteine, GPCR, PKM2, signaling pathways, immunotherapy, and NK-based therapy in pancreatic cancer.