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001 for both). CONCLUSIONS Patients with PIOL had increased OC width and volume than the healthy controls. An extra-wide olfactory cleft may be a predisposing factor in the pathogenesis of PIOL. LEVEL OF EVIDENCE 4 Laryngoscope, 2020. © 2020 The American Laryngological, Rhinological and Otological Society, Inc.PURPOSE With many plan variables to determine, manual forward planning for Gamma Knife (GK) radiosurgery is very challenging. Inverse planning eases GK planning by determining the variables via solving an optimization problem. However, due to the vast search space, most inverse planning algorithms, including the one provided in Leksell GammaPlan (LGP) treatment planning system, have to predetermine the isocenter locations using some geometric methods and then optimize the shot shapes and durations at these preselected isocenters. This sequential planning scheme does not necessarily lead to optimal isocenter locations and hence globally optimal plans. In this study, we proposed a multiresolution-level (MRL) inverse planning approach, attempting to approach this large-scale GK optimization problem via an iterative method. METHODS In our MRL approach, several rounds of optimizations were performed with a progressively increased resolution used for isocenter candidates. At each round, an optimization problem was case that have six targets, compared with manual planning and LGP inverse planning, our MRL approach achieved higher selectivity (0.68 vs 0.57 and 0.47) and lower gradient index (3.77 vs 4.51 and 5.11). The beam-on time of our plan was slightly longer than manual planning and LGP inverse planning (206.4 min vs 204.7 min and 199.3 min). We have also performed sector duration optimization at the isocenters determined by manual planning or the LGP inverse planning, and the resulting plan qualities were found to be inferior to our MRL approach for all the six cases. CONCLUSIONS This preliminary study has demonstrated the efficacy and feasibility of our MRL inverse planning approach for GK radiosurgery. © 2020 American Association of Physicists in Medicine.In this study, we characterized protease activities of 23 Ficus carica cultivars. Extracts of fruit, branch, and leaf of Masui Dauphine, one of the most representative F. carica cultivars in Japan, exhibited gelatin-hydrolyzing activity, both in the absence and presence of a cysteine protease-specific inhibitor, E-64, suggesting that not only ficin (classified as cysteine protease) but also collagenase (classified as serine protease) were involved in the digestion of gelatin. In the hydrolysis of (7-methoxycoumarin-4-yl)acetyl-l-Lys-l-Pro-l-Leu-Gly-l-Leu-[N3 -(2,4-dinitrophenyl)-l-2,3-diaminopropionyl]-l-Ala-l-Arg-NH2 , all branch extracts of 23 F. carica cultivars exhibited the activity both in the absence and presence of cysteine protease-specific inhibitor E-64, indicating that they contain ficin and collagenase. During digestion of acid-solubilized type I collagen by the branch extract of Masui Dauphine at 40-55 °C, collagen was completely digested in the absence of E-64, while it was partially digested in the presence of the inhibitor, indicating that the manner of digestion differed between ficin and collagenase contained in the extract. These results suggest that F. carica is attractive for industrial use to digest collagen. PRACTICAL APPLICATION The industrial use of F. carica might be enhanced by efficiently utilizing these proteases and/or selecting the appropriate F. carica cultivar. Collagen is one of the targets to which our results might be applied. It is widely accepted today that collagen and its digestion products could be useful as functional food. F. carica is a potential candidate for use in not only complete but also partial digestion of collagen. © 2020 Institute of Food Technologists®.PURPOSE The purpose of this study is to investigate the effect of different magnetic resonance (MR) sequences on the accuracy of deep learning-based synthetic computed tomography (sCT) generation in the complex head and neck region. METHODS Four sequences of MR images (T1, T2, T1C, and T1DixonC-water) were collected from 45 patients with nasopharyngeal carcinoma. Seven conditional generative adversarial network (cGAN) models were trained with different sequences (single channel) and different combinations (multi-channel) as inputs. To further verify the cGAN performance, we also used a U-net network as a comparison. Mean absolute error, structural similarity index, peak signal-to-noise ratio, dice similarity coefficient, and dose distribution were evaluated between the actual CTs and sCTs generated from different models. RESULTS The results show that the cGAN model with multi-channel (i.e., T1 + T2 + T1C + T1DixonC-water) as input to predict sCT achieves higher accuracy than any single MR sequence model. The T1-weighted MR model achieves better results than T2, T1C, and T1DixonC-water models. The comparison between cGAN and U-net shows that the sCTs predicted by cGAN retains additional image details are less blurred and more similar to the actual CT. CONCLUSIONS Conditional generative adversarial network with multiple MR sequences as model input shows the best accuracy. The T1-weighted MR images provide sufficient image information and are suitable for sCT prediction in clinical scenarios with limited acquisition sequences or limited acquisition time. MAPK inhibitor © 2020 American Association of Physicists in Medicine.The design of scaffolds for solubilizing/dispersing poorly water-soluble bioactive molecules in neutral aqueous media is a major challenge of functional food, pharmaceuticals, and cosmetics development, as highlighted by the plethora of corresponding solubilization/dispersion strategies. Herein, renatured β-1,3-1,6-glucan (r-glucan) nanoparticles prepared by neutralization of alkali-denatured β-1,3-1,6-glucan and subsequent centrifugation are used as a host to disperse water-insoluble bioactive molecules (curcumin, all-trans-retinoic acid, and rebamipide) by simple mixing of host and guest solutions. Curcumin in the r-glucan cavity is found to be stacked in the form of J-aggregates and twisted along the helix, and is demonstrated to be retained for significantly longer than curcumin in the corresponding γ-cyclodextrin (γ-CD) complex. Specifically, curcumin incorporated in γ-CD is released within 5.5 hours, whereas that in the r-glucan complex is released very slowly, with 12% of curcumin in the latter complex retained after 31-day incubation at 37°C.