Dexamethasone Pretreatment Potentiates a Folic Acid-Functionalized Delivery System for Enhanced Lung Cancer Therapy.

Folic acid (FA) has been widely engineered to promote the targeted delivery of FA-modified nanoparticles (NPs) by recognizing the folate receptor α (FRα). However, the efficacy of FA-targeted therapy significantly varied with the abundance of FRα and natural immunoglobulin levels in different tumors. Therefore, a sequential therapy of dexamethasone (Dex)-induced FRα amplification and immunosuppression combined with FA-functionalized doxorubicin (DOX) micelles to synergistically suppress tumor proliferation was proposed in this study. In brief, a pH/reduction-responsive FA-functionalized micelle (FCSD) was obtained by grafting FA, derivatization-modified cholesterol, and 2,3-dimethylmaleic anhydride onto a chitosan oligosaccharide. The obtained FCSD/DOX NPs can effectively deliver DOX in tumors, and their targeting efficiency can be further improved with Dex pretreatment to decrease the immunoglobulin M (IgM) content in serum and amplify FRα levels on the surface of M109 cells. After internalization, charge reversal and disulfide bond breakage of FCSD vectors under the stimulation of tumor extracellular pH (pHe) and intracellular glutathione (GSH) would contribute to the disintegration of vectors and the rapid release of DOX. The sequential therapy that combined Dex pretreatment and targeted chemotherapy by FCSD/DOX NPs demonstrated superior tumor suppression compared with monotherapy, which is expected to provide a potential strategy for FRα-positive lung cancer patients.

A supervised network for fast image-guided radiotherapy (IGRT) registration.

3D/3D image registration in IGRT, which aligns planning Computed Tomography (CT) image set with on board Cone Beam CT (CBCT) image set in a short time with high accuracy, is still a challenge due to its high computational cost and complex anatomical structure of medical image. In order to overcome these difficulties, a new method is proposed which contains a coarse registration and a fine registration. For the coarse registration, a supervised regression convolutional neural networks (CNNs) is used to optimize the spatial variation by minimizing the loss when combine the CT images with the CBCT images. For the fine registration, intensity-based image registration is used to calculate the accurate spatial difference of the input image pairs. A coarse registration can get a rough result with a wide capture range in less than 0.5 s. Sequentially a fine registration can get accurate results in a reasonable short time. RSD-111 T chest phantom was used to test our new method. The set-up error was calculated in less than 10s in time scale, and was reduced to sub-millimeter level in spatial scale. The average residual errors in translation and rotation are within ±0.5 mm and ± 0.2°.

Hypolipidemic effects of hickory nut oil using cold pressure extraction.

Optimal conditions of hickory nut oil cold press technology were studied. L9(34) orthogonal experiment results showed that optimal conditions were a pressing pressure of 15 MPa, pressing temperature of 50°C, pressing cycle of 4 s, and stop cycle of 9 s. Fatty acid compositions were determined using GC-MS and hypolipidemic effects in mice were investigated. Compared to a high fat diet group, hickory nut oil administration decreased serum and visceral total cholesterol, triacylglycerol, and serum low density lipoprotein cholesterol levels. Serum high density lipoprotein cholesterol values were increased. Hickory nut oil can be used as a valuable bioactive source of natural hypolipidemic compounds.