Background: To date, FM using middle ear packing has rarely reported. In this study, we hypothesized that middle ear packing with dexamethasone soaked gelfoam and fibrin glue over the fat graft could promote the success rate of TMP closure regardless of perforation size. Methods: Between January 2005 and July 2020, a total of 209 patients who underwent fat myringoplasty due to chronic TMP at tertiary referral center were encountered and analyzed. The success rate and audiologic outcome was analyzed. Results: The mean successful TM closure rate was 88.0 %. The success rate by different age generation was not significant difference. The size of the perforation grade showed no significant difference. The perforation site by anterior or posterior was not significant. The preoperative mean threshold of AC, BC and ABG were 55.71, 12.98 and 42.73 dB respectively. The postoperative mean threshold of AC, BC and ABG were 23.67, 12.98 and 10.69 dB. The change of preoperative and postoperative hearing showed statistically significant. Conclusion: From our results, the simple trimming of the perforation edge and middle ear packing with external ear canal packing using fibrin glue induced the stable adhesion between the remnant TM and the fat graft.

In recent years, there have been frequent reports on the adverse effects of synthetic cannabinoid (SC) abuse. SCs cause psychoactive effects, similar to those caused by marijuana, by binding and activating cannabinoid receptor 1 (CB1R) in the central nervous system. The aim of this study was to establish a reliable quantitative structure-activity relationship (QSAR) model to correlate the structures and physicochemical properties of various SCs with their CB1R-binding affinities. We prepared 15 SCs and their derivatives (tetrahydrocannabinol [THC], naphthoylindoles, and cyclohexylphenols) and determined their binding affinity to CB1R, which is known as a dependence-related target. We calculated the molecular descriptors for dataset compounds using an R/CDK (R package integrated with CDK, version 3.5.0) toolkit to build QSAR regression models. These models were established and statistical evaluations were performed using the mlr and plsr packages in R software. The most reliable QSAR model was obtained from the partial least squares regression method via external validation. This model can be applied in vivo to predict the addictive properties of illicit new SCs. Using a limited number of dataset compounds and our own experimental activity data, we built a QSAR model for SCs with good predictability. This QSAR modeling approach provides a novel strategy for establishing an efficient tool to predict the abuse potential of various SCs and to control their illicit use.