Investigation of Selected Flavonoid Derivatives as Potent FLT3 Inhibitors for the Potential Treatment of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is an aggressive disease with a poor prognosis and a high degree of relapse seen in patients. Overexpression of FMS-like tyrosine kinase 3 (FLT3) is associated with up to 70% of AML patients. Wild-type FLT3 induces proliferation and inhibits apoptosis in AML cells, while uncontrolled proliferation of FLT3 kinase activity is also associated with FLT3 mutations. Therefore, inhibiting FLT3 activity is a promising AML therapy. Flavonoids are a group of phytochemicals that can target protein kinases, suggesting their potential antitumor activities. In this study, several plant-derived flavonoids have been identified with FLT3 inhibitory activity. Among these compounds, compound 40 (5,7,4'-trihydroxy-6-methoxyflavone) exhibited the most potent inhibition against not only FLT3 (IC50 = 0.44 µM) but also FLT3-D835Y and FLT3-ITD mutants (IC50 = 0.23 and 0.39 µM, respectively). The critical interactions between the FLT3 binding site and the compounds were identified by performing a structure-activity relationship analysis. Furthermore, the results of cellular assays revealed that compounds 28, 31, 32, and 40 exhibited significant cytotoxicity against two human AML cell lines (MOLM-13 and MV-4-11), and compounds 31, 32, and 40 resulted in cell apoptosis and G0/G1 cell cycle arrest. Collectively, these flavonoids have the potential to be further optimized as FLT3 inhibitors and provide valuable chemical information for the development of new AML drugs.

Biological Evaluation of Selected Flavonoids as Inhibitors of MNKs Targeting Acute Myeloid Leukemia.

Excessive eIF4E phosphorylation by mitogen-activated protein kinase (MAPK)-interacting kinases 1 and 2 (MNK1 and MNK2; collectively, MNKs) has been associated with oncogenesis. The overexpression of eIF4E in acute myeloid leukemia (AML) is related to cancer cell growth and survival. Thus, the inhibition of MNKs and eIF4E phosphorylation are potential therapeutic strategies for AML. Herein, a structure-based virtual screening approach was performed to identify potential MNK inhibitors from natural products. Three flavonoids, apigenin, hispidulin, and luteolin, showed MNK2 inhibitory activity with IC50 values of 308, 252, and 579 nM, respectively. A structure-activity relationship analysis was performed to disclose the molecular interactions. Furthermore, luteolin exhibited substantial inhibitory efficacy against MNK1 (IC50 = 179 nM). Experimental results from cellular assays showed that hispidulin and luteolin inhibited the growth of MOLM-13 and MV4-11 AML cells by downregulating eIF4E phosphorylation and arresting the cell cycle at the G0/G1 phase. Therefore, hispidulin and luteolin showed promising results as lead compounds for the potential treatment for AML.

Automatic recognition of teeth and periodontal bone loss measurement in digital radiographs using deep-learning artificial intelligence.

Background/purpose: Artificial Intelligence (AI) can optimize treatment approaches in dental healthcare due to its high level of accuracy and wide range of applications. This study seeks to propose a new deep learning (DL) ensemble model based on deep Convolutional Neural Network (CNN) algorithms to predict tooth position, detect shape, detect remaining interproximal bone level, and detect radiographic bone loss (RBL) using periapical and bitewing radiographs. Materials and methods: 270 patients from January 2015 to December 2020, and all images were deidentified without private information for this study. A total of 8000 periapical radiographs with 27,964 teeth were included for our model. AI algorithms utilizing the YOLOv5 model and VIA labeling platform, including VGG-16 and U-Net architecture, were created as a novel ensemble model. Results of AI analysis were compared with clinicians' assessments. Results: DL-trained ensemble model accuracy was approximately 90% for periapical radiographs. Accuracy for tooth position detection was 88.8%, tooth shape detection 86.3%, periodontal bone level detection 92.61% and radiographic bone loss detection 97.0%. AI models were superior to mean accuracy values from 76% to 78% when detection was performed by dentists. Conclusion: The proposed DL-trained ensemble model provides a critical cornerstone for radiographic detection and a valuable adjunct to periodontal diagnosis. High accuracy and reliability indicate model's strong potential to enhance clinical professional performance and build more efficient dental health services.

Fabrication of Solvent-Free PCL/ß-TCP Composite Fiber for 3D Printing: Physiochemical and Biological Investigation.

Manufacturing three-dimensional (3D) objects with polymers/bioceramic composite materials has been investigated in recent years. In this study, we manufactured and evaluated solvent-free polycaprolactone (PCL) and beta-tricalcium phosphate (ß-TCP) composite fiber as a scaffold material for 3D printing. To investigate the optimal ratio of feedstock material for 3D printing, the physical and biological characteristics of four different ratios of ß-TCP compounds mixed with PCL were investigated. PCL/ß-TCP ratios of 0 wt.%, 10 wt.%, 20 wt.%, and 30 wt.% were fabricated, with PCL melted at 65 °C and blended with ß-TCP with no solvent added during the fabrication process. Electron microscopy revealed an even distribution of ß-TCP in the PCL fibers, while Fourier transform infrared spectroscopy demonstrated that the biomaterial compounds remained intact after the heating and manufacturing process. In addition, adding 20% ß-TCP into the PCL/ß-TCP mixture significantly increased hardness and Young's Modulus by 10% and 26.5%, respectively, suggesting that PCL-20 has better resistance to deformation under load. Cell viability, alkaline phosphatase (ALPase) activity, osteogenic gene expression, and mineralization were also observed to increase according to the amount of ß-TCP added. Cell viability and ALPase activity were 20% higher with PCL-30, while upregulation for osteoblast-related gene expression was better with PCL-20. In conclusion, PCL-20 and PCL-30 fibers fabricated without solvent exhibited excellent mechanical properties, high biocompatibility, and high osteogenic ability, making them promising materials for 3D printing customized bone scaffolds promptly, sustainably, and cost-effectively.