Adaptive condition-aware high-dimensional decoupling remote sensing image object detection algorithm.

Remote Sensing Image Object Detection (RSIOD) faces the challenges of multi-scale objects, dense overlap of objects and uneven data distribution in practical applications. In order to solve these problems, this paper proposes a YOLO-ACPHD RSIOD algorithm. The algorithm adopts Adaptive Condition Awareness Technology (ACAT), which can dynamically adjust the parameters of the convolution kernel, so as to adapt to the objects of different scales and positions. Compared with the traditional fixed convolution kernel, this dynamic adjustment can better adapt to the diversity of scale, direction and shape of the object, thus improving the accuracy and robustness of Object Detection (OD). In addition, a High-Dimensional Decoupling Technology (HDDT) is used to reduce the amount of calculation to 1/N by performing deep convolution on the input data and then performing spatial convolution on each channel. When dealing with large-scale Remote Sensing Image (RSI) data, this reduction in computation can significantly improve the efficiency of the algorithm and accelerate the speed of OD, so as to better adapt to the needs of practical application scenarios. Through the experimental verification of the RSOD RSI data set, the YOLO-ACPHD model in this paper shows very satisfactory performance. The F1 value reaches 0.99, the Precision value reaches 1, the Precision-Recall value reaches 0.994, the Recall value reaches 1, and the mAP value reaches 99.36 % , which indicates that the model shows the highest level in the accuracy and comprehensiveness of OD.

Discovery of BI 135585, an in vivo efficacious oxazinanone-based 11ß hydroxysteroid dehydrogenase type 1 inhibitor.

A potent, in vivo efficacious 11ß hydroxysteroid dehydrogenase type 1 (11ß HSD1) inhibitor (11j) has been identified. Compound 11j inhibited 11ß HSD1 activity in human adipocytes with an IC50 of 4.3nM and in primary human adipose tissue with an IC80 of 53nM. Oral administration of 11j to cynomolgus monkey inhibited 11ß HSD1 activity in adipose tissue. Compound 11j exhibited >1000× selectivity over other hydroxysteroid dehydrogenases, displays desirable pharmacodynamic properties and entered human clinical trials in 2011.

Structure-based design and synthesis of 1,3-oxazinan-2-one inhibitors of 11ß-hydroxysteroid dehydrogenase type 1.

Structure based design led directly to 1,3-oxazinan-2-one 9a with an IC(50) of 42 nM against 11ß-HSD1 in vitro. Optimization of 9a for improved in vitro enzymatic and cellular potency afforded 25f with IC(50) values of 0.8 nM for the enzyme and 2.5 nM in adipocytes. In addition, 25f has 94% oral bioavailability in rat and >1000× selectivity over 11ß-HSD2. In mice, 25f was distributed to the target tissues, liver, and adipose, and in cynomolgus monkeys a 10 mg/kg oral dose reduced cortisol production by 85% following a cortisone challenge.

Discovery and optimization of adamantyl carbamate inhibitors of 11ß-HSD1.

Synthesis of 2-adamantyl carbamate derivatives of piperidines and pyrrolidines led to the discovery of 9a with an IC(50) of 15.2 nM against human 11ß-HSD1 in adipocytes. Optimization for increased adipocyte potency, metabolic stability and selectivity afforded 11k and 11l, both of which were >25% orally bioavailable in rat.

Spirocyclic ureas: orally bioavailable 11 beta-HSD1 inhibitors identified by computer-aided drug design.

Structure-guided drug design led to the identification of a class of spirocyclic ureas which potently inhibit human 11beta-HSD1 in vitro. Lead compound 10j was shown to be orally bioavailable in three species, distributed into adipose tissue in the mouse, and its (R) isomer 10j2 was efficacious in a primate pharmacodynamic model.