Recent studies on sphingolipids suggest that acid sphingomyelinase (ASM), which plays a central role in the pathogenesis of major depression, is emerging to be a novel target for developing antidepressants. Herein we first described the design, synthesis, and biological evaluation of hydroxamic acid-based direct inhibitors of ASM with the effort of validating their antidepressant effects in vivo. As a result, a series of novel ASM inhibitors were developed using a structure-based approach. Our studies demonstrated that the administration of 21b improved depression-like behaviors of rats. Importantly, this positive result was relevant to the inhibition of ASM and the increasing neurogenesis in hippocampus. To the best of our knowledge, this is the first time that direct inhibitors of ASM were developed to support the possibility of ASM as a potential therapeutic target for depression.
To fulfill the requirement of fields such as robotics, aviation, and special machining, motors with quill shafts or outer rotors have been used. For these special motors, the photoelectric encoder’s volume is normally too big and easy to be polluted by oil or dust; magnetic encoder normally has poor accuracy, and alnico piece may not provide enough magnetic field coverage area. The aim of this essay is to find a new structure of magnetic encoder to improve the precision and magnetic field coverage area. By using two multi-pole alnico rings with a different number of pole pairs to provide a magnetic field, the coverage area could be improved. The position differences between two alnicos pole positions are used to calculate absolute angle value, so the accuracy of the encoder could be absolute and no less than that of a combined magnetic encoder with the same number of pole pairs. A special algorithm is proposed for decoding. This new kind of magnetic encoder could be used on special motors with quill shafts or outer rotors. Its volume and weight are less than the photoelectric encoder and have better performance on antipollution. The alnico ring is easy to modify to suit the structure of the motor.
The severe side effects of chemosynthetic anti-diarrhea drugs have created an interest in low-toxic alternative plant-derived compounds. FengLiao consists of Polygonum hydropiper Linn. and Daphniphyllum calycinum Bench., and is widely used in China to treat diarrhea due to low levels of toxicity. In this study, the effects of FengLiao were analyzed in a castor oil-induced diarrhea model, using the anti-diarrhea drug, loperamide, as the positive control. The effects were evaluated using stool characteristics and the expression levels of various diarrhea-related factors in the jejunum and liver, as well as changes in the microbiota of the jejunum. The symptoms of diarrhea and stool consistency were improved through FengLiao and loperamide treatment. Furthermore, FengLiao down-regulated alpha 1-acid glycoprotein (AGP) and C-reactive protein (CRP) levels, and up-regulated transferrin (TRF) mRNA levels in the liver, and down-regulated Aquaporin 3 (AQP3) and Na+/H+ exchanger isoform 8 (NHE8) expression in the epithelial cells of the jejunum. It also increased the relative abundance of Bifidobacterium, Aerococcus, Corynebacterium_1 and Pseudomonas, and lowered the Firmicutes/Bacteroidetes (F/B) ratio, which maintained the balance between immunity and intestinal health. Taken together, FengLiao alleviated castor oil-induced diarrhea by altering gut microbiota, and levels of jejunum epithelial transport proteins and acute phase proteins.
A selective recursive kernel learning-based (SRKL) adaptive predictive controller is proposed for nonlinear timevarying processes. First, a SRKL identification model is presented with an efficient sparsification strategy which makes a trade-off between the tracking precision and the controller's complexity. The SRKL model can be updated efficiently by introducing and/or deleting a sample via recursive learning algorithms. Consequently, the model can adjust its structure adaptively to capture the process dynamics and time-varying characteristics. On the basis of the SRKL model, a predictive controller with an adaptive modification item is designed. The novel controller can achieve better performance since the SRKL model can trace the process characteristics online. The obtained results on a laboratory-scale liquid-level process and a continuous bioreactor with time-varying parameters show that the proposed controller is superior to the traditional proportional-integral-derivative (PID) controller and related controller with an offline KL model without online updating.
A new low-loss high-index-contrast photonics platform has been developed for integrated optics and microwave photonics. The platform consists of a material system that has an index contrast that is adjustable from 0 to 25% and which is processed using conventional CMOS tools. The platform allows one to four orders of magnitude reduction in the size of optical components compared with conventional planar technologies. As an example, meter long path lengths occupy coils that are millimeters in diameter. Microwave photonic building blocks that are enabled include large bit count programmable delay lines for beam steering and shaping that fit in less than a square centimeter and which have delays controllable from 5 fsec to 10 nsec. Also enabled are arrays of high order tunable filters, a hundred micrometers in size, having linewidths ranging from tens of MHz to tens of GHz. These filters can be tuned over several hundred GHz, and when placed in Vernier architectures can be tuned across the C band (5 THz). An optical chip typically consists of dozens of optical elements. Each element is placed in its own micro-control loop that consists of a thin film heater for thermo-optic control and a thermistor for electronic feedback. The micro-control loops impart intelligence to the optical chip.
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