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Abstract Background NGF-TrkA is well known to play a key role in propagating and sustaining pruritogenic signals, which form the pathology of chronic pruritus. Inhibition of NGF-TrkA is a known strategy for the treatment of pruritus. In the present paper, we describe the identification, in vitro characterization, structure–activity analysis, and inhibitory evaluation of a novel TrkA inhibitory scaffold exemplified by Cucurbitacins (Cus). Methods Cus were identified as TrkA inhibitors in a large-scale kinase library screen. To obtain structural models of Cus as TrkA inhibitors, AutoDock was used to explore their binding to TrkA. Furthermore, PC12 cell culture systems have been used to study the effects of Cus and traditional Chinese medicinal plants (Tian Gua Di and bitter gourd leaf) extracts on the kinase activity of TrkA. Results Cus block the phosphorylation of TrkA on several tyrosine sites, including Tyr490, Tyr674/675, and Tyr785, and inhibit downstream Akt and MAPK phosphorylation in response to NGF in PC12 cell model systems. Furthermore, traditional Chinese medicinal plants (Tian Gua Di and bitter gourd leaf) containing Cu extracts were shown to inhibit the phosphorylation of TrkA and Akt. These data reveal mechanisms, at least partly, of the anti-pruritus bioactivity of Cus. Conclusion Taken together, with the recent discovery of the important role of TrkA as a therapeutic target, Cus could be the basis for the design of improved TrkA kinase inhibitors, which could someday help treat pruritus.

Honokiol (HK) usage is greatly restricted by its poor aqueous solubility and limited oral bioavailability. We synthesized and characterized a novel phosphate prodrug of honokiol (HKP) for in vitro and in vivo use. HKP greatly enhanced the aqueous solubility of HK (127.54 ± 15.53 mg/ml) and the stability in buffer solution was sufficient for intravenous administration. The enzymatic hydrolysis of HKP to HK was extremely rapid in vitro (T1/2 = 8.9 ± 2.11 s). Pharmacokinetics studies demonstrated that after intravenous administration of HKP (32 mg/kg), HKP was converted rapidly to HK with a time to reach the maximum plasma concentration of ∼5 min. The prodrug HKP achieved an improved T1/2 (7.97 ± 1.30 h) and terminal volume of distribution (26.02 ± 6.04 ml/kg) compared with direct injection of the equimolar parent drug (0.66 ± 0.01 h) and (2.90 ± 0.342 ml/kg), respectively. Furthermore, oral administration of HKP showed rapid and improved absorption compared with the parent drug. HKP was confirmed to maintain the bioactivity of the parent drug for ameliorating ischemia-reperfusion injury by decreasing brain infarction and improving neurologic function. Taken together, HKP is a potentially useful aqueous-soluble prodrug with improved pharmacokinetic properties which may merit further development as a potential drug candidate. Keywords: Phosphate prodrug, Honokiol, Pharmacokinetics, Focal cerebral ischemia-reperfusion

To address the problems of the suspended buffer spring’s safety and service life, we introduce the basic operating principles and structure parameters of the suspended buffer; followed by establishing a new numerical model of the buffer spring vibration using Femap software. The vibration characteristics of the spring form the basis for spring safety check and service life prediction. Therefore, the principles influencing the gangue particle size and feeding rate on the vibration characteristics of the buffer spring were analyzed. The results have indicated that the vibration frequency, axial pressure peak and the maximum and minimum axial pressure within the periodic vibration had power relations with gangue particle size D, while they had linear relations with the gangue feeding rate v except for the vibration frequency that had nothing to do with the feeding rate. According to the ultimate axial pressure of the spring, the relations between the shear pressure and tensile strength as well as the vibration characteristics, the spring’s safety check formula and service life formula were obtained. Based on the backfilling parameters of the working face in Dongping Coal Mine, the crushed gangue particle size and spring service life were determined. Based on the engineering practice in Dongping Coal Mine, the spring service life was obtained. And the fatigue fracture of the spring was also analyzed.

Aiming at the problem of the sudden increase of the working resistance of the support in the transition section of the mixed workface, this paper adopts the physical simulation to study the fracture and movement characteristics of the overburden strata in the backfilling section and the caving section after analysis of the system layout of mixed workface. Then, the definition of the transition section of the mixed workface is given. Next, a numerical model of the transition section length is established based on the geological conditions of the Ji15-31010 mixed workface of Pingdingshan No.12 Coal Mine. In the numerical simulation, it is used to study the influence of the advancing length of the mixed workface and the length of the backfilling section on the transition section length. The results show that with the increase of the advancing length of the mixed workface and the decrease of the backfilling section length, the transition section length increases continuously and eventually stabilizes. The range of variation is 6.2~13.5 m, corresponding to 4~9 hydraulic supports with a width of 1.5 m. Based on the above conclusions and the price of transitional hydraulic supports, the 4 transitional hydraulic supports used in the transition section of the Ji15-31010 mixed workface is determined. Filed measurement shows that as the mixed workface is advanced from 10 m to 40 m, the transition section length increases from 2 supports to 4 supports, and decreases to 2 supports again when advanced to 60 m. This indicates that the main roof of the mixed workface between 40 and 60 m experiences the initial caving. The maximum length of the transition section is 6.0 m, corresponding to 4 hydraulic supports.

Mutation-based greybox fuzzing is a highly effective and widely used technique to find bugs in software. Provided initial seeds, fuzzers continuously generate test cases to test the software by mutating a seed input. However, the majority of them are “invalid” because the mutation may destroy the format of the seeds. In this paper, we present a knowledge-learn evolutionary fuzzer based on AFL, which is called LearnAFL. LearnAFL does not require any prior knowledge of the application or input format. Based on our format generation theory, LearnAFL can learn partial format knowledge of some paths by analyzing the test cases that exercise the paths. Then LearnAFL uses these format information to mutate the seeds, which is efficient to explore deeper paths and reduce the test cases exercising high-frequency paths than AFL. We compared LearnAFL with AFL and some other state-of-the-art fuzzers on ten real-world programs. The result showed that LearnAFL could reach branch coverage 120% and 110% of that of AFL and FairFuzz, respectively. LearnAFL also found 8 unknown vulnerabilities in GNU Binutils, Libpng and Gif2png, all of which have been reported to the vendors. Besides, we compared the format information learned from the initial seed of an ELF file with a format standard of ELF files. The result showed that LearnAFL learns about 64% part of the file format without any prior knowledge.

The Internet of Things (IoT) is widely regarded as a key component of the Internet of the future and thereby has drawn significant interests in recent years. IoT consists of billions of intelligent and communicating “things”, which further extend borders of the world with physical and virtual entities. Such ubiquitous smart things produce massive data every day, posing urgent demands on quick data analysis on various smart mobile devices. Fortunately, the recent breakthroughs in deep learning have enabled us to address the problem in an elegant way. Deep models can be exported to process massive sensor data and learn underlying features quickly and efficiently for various IoT applications on smart devices. In this article, we survey the literature on leveraging deep learning to various IoT applications. We aim to give insights on how deep learning tools can be applied from diverse perspectives to empower IoT applications in four representative domains, including smart healthcare, smart home, smart transportation, and smart industry. A main thrust is to seamlessly merge the two disciplines of deep learning and IoT, resulting in a wide-range of new designs in IoT applications, such as health monitoring, disease analysis, indoor localization, intelligent control, home robotics, traffic prediction, traffic monitoring, autonomous driving, and manufacture inspection. We also discuss a set of issues, challenges, and future research directions that leverage deep learning to empower IoT applications, which may motivate and inspire further developments in this promising field.

In this study, a high-photoresponsivity self-powered deep ultraviolet (DUV) photodetector based on an Ag2O/β-Ga2O3 heterojunction was fabricated by depositing a p-type Ag2O thin film onto an n-type β-Ga2O3 layer. The device characteristics after post-annealing at temperatures ranging from 0 to 400 °C were investigated. Our DUV devices exhibited typical rectification characteristics. At a post-annealing temperature of 300 °C, the as-fabricated device had a low leakage current of 4.24 × 10−11 A, ideality factor of 2.08, and a barrier height of 1.12 eV. Moreover, a high photo-responsivity of 12.87 mA/W was obtained at a 100 μW/cm2 light intensity at a 254 nm wavelength at zero bias voltage, the detectivity was 2.70 × 1011 Jones, and the rise and fall time were 29.76, 46.73 ms, respectively. Based on these results, the Ag2O/β-Ga2O3 heterojunction photodetector operates without an externally applied voltage and has high responsivity, which will help in the performance improvement of ultraviolet sensing systems.

Background Cardiac arrest (CA) can induce oxidative stress after resuscitation, which causes cellular and organ damage. We hypothesized that post‐resuscitation normoxic therapy would protect organs against oxidative stress and improve oxygen metabolism and survival. We tested the oxygen‐sensitive reactive oxygen species from mitochondria to determine the association with hyperoxia‐induced oxidative stress. Methods and Results Sprague–Dawley rats were subjected to 10‐minute asphyxia‐induced CA with a fraction of inspired O2 of 0.3 or 1.0 (normoxia versus hyperoxia, respectively) after resuscitation. The survival rate at 48 hours was higher in the normoxia group than in the hyperoxia group (77% versus 28%, P

In recent years, since portable devices with thin and light designs are essential, the applications of the thin-film transistor liquid crystal display (TFT-LCD) have been applied extensively. Process yield is the most common criterion used in the TFT-LCD manufacturing industry for measuring process performance. The measurement index Spk establishes the relationship between the manufacturing specifications and the actual process performance, which provides an exact measure on process yield. In this paper, we provide two convenient ratio approaches to calculate the lower confidence bounds and critical values extensively for various values of α-risk, capability requirements, and sample sizes. Practitioners can use the proposed ratio approaches and procedures to determine whether their process meets the preset capability requirement and make reliable decisions. The convenient ratio approaches can bridge the gap between the theoretical development and factory applications for evaluation of process yields. [ABSTRACT FROM AUTHOR]