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Through a modified Kinugasa reaction, a novel method of amidation on terminal oligo alkyne conjugates by copper-promoted oxidation with nitrones has been developed. Unprotected bifunctional carboxylic acid-amine reagents can be transformed directly to the respective amide products under these edited Kinugasa reaction conditions. 3-Cycle DNA-encoded libraries (DELs) can be built in three steps of chemical conversion.

Limited by 4battery capacity, advanced microcontroller units (MCUs) for Internet of Things (IoT) applications require ultra-low power consumption. In a conventional design, the sleep power accounts for most of the total power consumption, and cannot be reduced further due to the low power efficiency of dc-dc converters at the load current ~100 nA. Voltage stacking has been proposed to address power efficiency. However, prior voltage-stacking architectures could not realize dynamic switching between flat mode and stack mode, leading to high dynamic power consumption in the normal state. This article proposes a dynamic voltage-stacking scheme, which supports two operating modes: a flat mode in the normal state and a stack mode in the sleep state. In the flat mode, the retention memories, RTC and XO32, are connected in parallel and are powered by the switched-capacitor voltage regulator (SCVR). In the stack mode, the four instances are connected in series, including the static random access memory (SRAM1) (level1), the SRAM2 (level2), and the XO32 and the RTC (level3), and the on-chip SCVR is shut down for power saving. The measurements show that compared with the conventional flat architecture, the dynamic voltage-stacking scheme reduces the sleep current by 38% under the same circumstances, and it also improves ULPMark-CP score by 23.6%, which is higher than the top1 in the ULPMark score list.

The secant modulus reflects the ability of rocks to resist deformation, and it is mostly used to evaluate rock strength and deformation evolution. Due to the existence of rough joints in rocks, the secant modulus changes according to rock size. Therefore, it is very important to effectively obtain the secant modulus to evaluate rough-jointed rock deformation. In this paper, the regression analysis method is used, and 25 sets of simulation models are set up to discuss the influence of joint roughness and rock size on the rock secant modulus. The research shows that the secant modulus increases exponentially with the increase in rock size, and it increases as a power function with the increase in joint roughness. The characteristic size of the secant modulus increases exponentially with the increase in joint roughness, also as a power function. This paper gives the specific forms of these four relationships. The establishment of these relationships enables the prediction and calculation of the secant modulus and provides guidance for rock deformation analysis.

Hearing is one of the most important human perception forms, and humans can capture the movement of sound in complex environments. On the basis of this phenomenon, this study explored the possibility of eliciting a steady-state brain response in an intermittent periodic motion sound source. In this study, a novel discrete continuous and orderly change of sound source positions stimulation paradigm was designed based on virtual sound using head-related transfer functions (HRTFs). And then the auditory motion stimulation paradigms with different noise levels were designed by changing the signal-to-noise ratio (SNR). The characteristics of brain response and the effects of different noises on brain response were studied by analyzing electroencephalogram (EEG) signals evoked by the proposed stimulation. Experimental results showed that the proposed paradigm could elicit a novel steady-state auditory evoked potential (AEP), i.e., steady-state motion auditory evoked potential (SSMAEP). And moderate noise could enhance SSMAEP amplitude and corresponding brain connectivity. This study enriches the types of AEPs and provides insights into the mechanism of brain processing of motion sound sources and the impact of noise on brain processing.

Improved in situ hybridization methods for mRNA detection in tissues have been developed based on the hybridization chain reaction (HCR). We show that in situ HCR methods can be used for the detection of microRNAs in tissue sections from mouse retinas. In situ HCR can be used for the detection of two microRNAs simultaneously or for the combined detection of microRNA and mRNA. In addition, miRNA in situ HCR can be combined with immunodetection of proteins. We use these methods to characterize cells expressing specific microRNAs in the mouse retina. We find that miR-181a is expressed in amacrine cells during development and in adult retinas, and it is present in both GABAergic and glycinergic amacrine cells. The detection of microRNAs with in situ HCR should facilitate studies of microRNA function and gene regulation in the retina and other tissues.

Aims: Lysine acetyltransferase 6B (KAT6B), is a histone acetyltransferase implicated to have a role in tumor suppression. However, the relationship between KAT6B and hepatocellular carcinoma (HCC) is unclear. The purpose of this study was to detect the expression of KAT6B in HCC tissues and analyze its connection with the clinicopathological features of HCC. Methods: First, we performed immunohistochemical staining on 250 HCC tissues and 222 non-tumor liver tissues to examine the expression of KAT6B.Then the relation between KAT6B expression and clinicopathological parameters was analyzed by chi-square test, and the overall survival analysis was conducted by Kaplan-Meier survival method. In addition, based on the Oncomine expression array online and the UALCAN database, we compared KAT6B expression differences between normal liver tissues and HCC tissues more broadly. Results: Compared with normal tissues, KAT6B expression was significantly lower in HCC tissues. Low KAT6B expression was found to be related to gender, AFP level, and tumor size. According to the online database, KAT6B expression was found to be decreased in HCC tissues and high in normal tissues. Conclusions: Lower expression of KAT6B is associated with poor prognosis of HCC, and KAT6B may be a potential tumor suppressor in liver cancer.

Due to the bypass of muscle activity or peripheral nerve control, brain-computer interface (BCI) technique has advantages in different fields such as medical field for the rehabilitation of paralyzed patients. Steady-state visual evoked potential (SSVEP) has been widely adopted in BCI applications. SSVEP based BCIs have the advantages of high information transfer rate, less or no need of training, and strong anti-interference, which could be used in the more natural asynchronous BCI application with control of the users rather than the operant system of the synchronous mode. In order to solve the problem of high false positive rate (FPR) in common asynchronous SSVEP BCI applications, this paper proposed an eye-tracking switch based BCI paradigm to reduce the FPR and to improve the performance of the asynchronous BCI system. In the proposed paradigm, the fixation point position instead of EEG signal is used to determine whether the system is in idle state. Experimental results showed that when eye-tracking switch was applied in the asynchronous SSVEP BCI, the FPR was reduced to less than 10% and the recognition accuracy (i.e., the true positive rate, TPR) can also be improved to a certain extent, which proved the applicability of the eye-tracking switch in asynchronous BCI applications.

In recent years, object detection in remote sensing imagery has attracted more and more attention. Accurate object detection in remote sensing imagery, especially for small objects, is still challenging. Most existing methods utilize the global information in the deep fully convolution layer and neglect the local information in the input image. However, the local information contains sufficient spatial information, which is beneficial for precise localization. Additionally, there still exists variable factors, such as the arbitrary aspect ratio and rotation, which interfere the object detection performance. To solve these problems mentioned above, we propose a novel multi-scale structure-conditioned feature transform network, which adopts FCOS as the baseline and ATSS as the method for training sample selection. On one hand, structural information is extracted to represent the spatial semantic information. On the other hand, multi-scale information is enhanced through a novel hierarchical residual-in-residual module. Experiments on the HRRSD data set have demonstrated the superiority of our method.

In this study, the complete mitochondrial genome of Leuciscus waleckii waleckii was sequenced and got a whole length of 16605 bp. This genome was contain 2 rRNA, 22 tRNA, 13 protein-coding genes, 1 control region (D-loop) and 1 replication origin. And the nucleotide composition of this mitochondrial genome is 27.72% for A, 26.28% for T, 27.23% for C and 18.77% for G. To clarify the phylogenetic relationship of the Leuciscus waleckii waleckii, we concluded the phylogenetic tree using 12 PCGs (except ND6) of mitochondrial genome in Leuciscus waleckii waleckii and 16 other cyprinid fish by Bayesian inference (BI) methods and maximum-likelihood (ML). And the result show that Leuciscus waleckii waleckii was close to other Leuciscus species, especially Leuciscus baicalensis.

Background: SN38 (7-ethyl-10-hydroxy camptothecin), as a potent metabolite of irinotecan, is highly efficacious in cancer treatment. However, the clinical utility of SN38 has been greatly limited due to its undesirable properties, such as poor solubility and low stability. Materials and methods: In order to overcome these weaknesses, moeixitecan, a lipophilic SN38 prodrug containing a SN-38, a trolox, a succinic acid linker, and a hexadecanol chain, was loaded into liposomal nanoparticles by ethanol injection method. Results: Experiments showed that the moeixitecan-loaded liposomal nanoparticles (MLP) with a diameter of 105.10±1.49 nm have a satisfactory drug loading rate (90.54±0.41%), high solubility and stability, and showed sustained release of SN38. Notably, MLP exhibited better antitumor activity against human colon adenocarcinoma cells than irinotecan, a FDA-approved drug for the treatment of advanced colorectal cancer. Furthermore, xenograft model results showed that MLP outperformed irinotecan in terms of pharmacokinetics, in vivo therapeutic efficacy and safety. Finally, we used molecular dynamic simulations to explore the association between the structure of MLP and the physical and functional properties of MLP, moeixitecan molecules in MLP folded themselves inside the hydrocarbon chain of the lipid bilayer, which led an increased acyl chain order of the lipid bilayer, and therefore enhanced the lactone ring stability protecting it from hydrolysis. Conclusion: Our MLP constructing strategy by liposome engineering technology may serve a promising universal approach for the effective and safe delivery of lipophilic prodrug.

In this paper, a novel microwave power detection system based on Schottky diode is constructed in order to measure microwave power in the LTE-band (1.8~2.7 GHz). The proposed detection system is consisted of three modules: a collecting module, a measuring module, and a processing module. Among them, a microwave power detection circuit based on Schottky diode is developed to realize the high-quality conversion of microwave power signal to voltage signal. The experimental results reveal that the presented system has good linearity. In the range of 1.8~2.7 GHz, the incident microwave power is increased from 1 uW to 50 mW, and the sensitivity of the detection system is 1.86 mV/uW at 2.0 GHz, 1.61 mV/uW at 2.3 GHz, and 1.2 mV/uW at 2.6 GHz, which is much better than other microwave power sensors. Therefore, the microwave power detection system based on Schottky diode provides an effective solution for microwave power detection in the LTE-band.

For the problem that the standard probability hypothesis density is unable to correctly estimate the states of targets and their number when tracking multiple targets in possible missed detection environments, an improved probability hypothesis density filter based multi-target tracking algorithm is proposed under the linear Gaussian conditions. Two assisted parameters, namely label and probability of existence, are introduced to expand the standard target state in the proposed algorithm which includes three robust schemes compared with the Gaussian mixture probability hypothesis density filter. Firstly, the extended component set of target states representing the target intensity can be correctly updated in the proposed target intensity update scheme. Secondly, by optimizing the component set that approximates the target posterior intensity, the excess and invalid components are effectively reduced in the improved component fusion scheme. Lastly, a new target state extraction scheme is able to accurately estimate the states of targets by comprehensively utilizing both the weight and existent probability of the target. Simulation results show that the proposed algorithm not only provides relatively accurate multi-target estimates, but also has a relatively low computational burden.

The mammalian retina contains a complex mixture of different types of neurons. We find that microRNA miR-216b is preferentially expressed in postmitotic retinal amacrine cells in the mouse retina, and expression of miR-216a/b and miR-217 in retina depend in part on Ptf1a, a transcription factor required for amacrine cell differentiation. Surprisingly, ectopic expression of miR-216b directed the formation of additional amacrine cells and reduced bipolar neurons in the developing retina. We identify the Foxn3 mRNA as a retinal target of miR-216b by Argonaute PAR-CLIP and reporter analysis. Inhibition of Foxn3, a transcription factor, in the postnatal developing retina by RNAi increased the formation of amacrine cells and reduced bipolar cell formation. Foxn3 disruption by CRISPR in embryonic retinal explants also increased amacrine cell formation, whereas Foxn3 overexpression inhibited amacrine cell formation prior to Ptf1a expression. Co-expression of Foxn3 partially reversed the effects of ectopic miR-216b on retinal cell formation. Our results identify Foxn3 as a novel regulator of interneuron formation in the developing retina and suggest that miR-216b likely regulates Foxn3 and other genes in amacrine cells.

The Eyebrowed Thrush (Turdus obscurus) is a highly migratory bird, which breeds in northeastern Asia and overwinters in southeastern Asia. We obtained the mitochondrial genome of T. obscurus by Sanger sequencing. The mitogenome was 16,739 bp in length, which contains 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and one control region. Its composition is consistent with the species in genus Turdus. Phylogenetic analysis based on the whole mitochondrial genome showed that the relationship between T. obscurus and Turdus kessleri was relatively close. This study improves the understanding of phylogeny and genetics of Turdidae and Muscicapoidea.

The mammalian retina contains a complex mixture of different types of neurons. We find that the microRNA miR-216b is preferentially expressed in postmitotic retinal amacrine cells in the mouse retina, and expression of miR-216a/b and miR-217 in the retina depend in part on Ptf1a, a transcription factor required for amacrine cell differentiation. Surprisingly, ectopic expression of miR-216b, or the related miR-216a, can direct the formation of additional amacrine cells in the developing retina. In addition, we observe the loss of bipolar neurons in the retina after miR-216b expression. We identify the mRNA for the transcriptional regulator Foxn3 as a retinal target of miR-216b by Argonaute PAR-CLIP and reporter analysis. Inhibition of Foxn3 in the postnatal developing retina by RNAi also increases the formation of amacrine cells and reduces bipolar cell formation, while overexpression of Foxn3 inhibits amacrine cell formation prior to the expression of Ptf1a. Disruption of Foxn3 by CRISPR in embryonic retinal explants also reduces amacrine cell formation. Co-expression of Foxn3 can partially reverse the effects of ectopic miR-216b on retinal cell type formation. Our results identify Foxn3 as a novel regulator of interneuron formation in the developing retina and suggest that miR-216b likely regulates expression of Foxn3 and other genes in amacrine cells.

Background Citron kinase (CIT) is a protein related to cytokinesis and is an important abscission regulator. However, the relationship between CIT and hepatocellular carcinoma (HCC) is unclear. The aim of this study was to investigate the expression CIT in HCC tissues, and explore the connection between this expression and clinicopathological characteristics of HCC. Methods Immunohistochemistry staining on 235 HCC tissues and 96 non-tumorous liver tissues controls was performed to examine the CIT protein expression. We then analyzed the correlation between protein expression and clinicopathological parameters via χ2 tests, and we performed overall survival analyses via the Kaplan-Meier survival approach. Based on the online Oncomine Expression Array and UALCAN databases, we more broadly compared CIT mRNA expression between normal and HCC tissues. Finally, we compared CIT mRNA expression in these databases to protein expression in our study and explored potential sources for any observe differences. Results Compared to normal tissues, CIT expression was significantly lower in HCC tissues. Low CIT expression was found to be related to gender, tumor size, Edmondson Grade, Microvascular invasion, serum AFP levels and poor overall survival. Based on the online databases, CIT mRNA expression was found to be high in HCC tissues and decreased in normal tissues. We hypothesize that this unexpected result is due to a negative feedback loop whereby low protein CIT levels mediate increased CIT mRNA levels. Conclusions Lower CIT protein levels are associated with a poorer prognosis in HCC patients, and lower CIT protein levels may mediate a negative feedback loop leading to increased CIT mRNA levels.

Probability hypothesis density (PHD) filter is a suboptimal Bayesian multi-target filter based on random finite set. The Gaussian mixture PHD filter is an analytic solution to the PHD filter for linear Gaussian multi-target models. However, when targets move near each other, the GM-PHD filter cannot correctly estimate the number of targets and their states. To solve the problem, a novel reweighting scheme for closely spaced targets is proposed under the framework of the GM-PHD filter, which can be able to correctly redistribute the weights of closely spaced targets, and effectively improve the multiple target state estimation precision. Simulation results demonstrate that the proposed algorithm can accurately estimate the number of targets and their states, and effectively improve the performance of multi-target tracking algorithm.

Probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data association between measurements and tracks. The Gaussian mixture (GM) implementation of the PHD filter is a closed-form solution to the PHD filter for linear Gaussian model. However, the Gaussian mixture PHD filter suffers from filtering performance degradation problem in multi-target tracking scenarios with low probability of detection, especially when it comes to tracking nearby targets in the imperfect probability of detection conditions. Aiming at the problem, a robust Gaussian mixture PHD algorithm for tracking multiple targets is proposed. First, a novel nearby target tracking method is introduced to reallocate the possible incorrect weights of the nearby targets. Then, a novel target state estimation scheme, making full use of the multiple previous weights of the targets, is adopted to extract the estimates of the target states. Simulation experiments have demonstrated that the proposed approach can achieve better performance in terms of target states and their number than the other related algorithms when tracking multiple nearby targets in the low probability of detection scenarios.

The Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter is a promising approach for tracking an unknown number of extended targets. However, it does not achieve satisfactory performance if targets in different sizes are spatially close and manoeuvring because the partitioning methods are sensitive to manoeuvres. To solve this problem, the authors propose the shape selection partitioning (SSP) measurement partitioning algorithm. The proposed algorithm first calculates potential centres and shapes of targets. It then combines each centre with different shapes to divide measurements into subcells. Accordingly, some candidate partitions can be obtained. Finally, it selects the most likely candidate partition and outputs the corresponding subcells. Simulation results show that the application of SSP to the GIW-PHD filter can achieve better performance when targets are spatially close and manoeuvring, which leads to a lower optimal subpattern assignment distance and a higher accuracy of the sum of weights.

The probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data associations between the measurements and targets. However, the target birth intensity as a prior is assumed to be known before tracking in a traditional target-tracking algorithm; otherwise, the performance of a conventional PHD filter will decline sharply. Aiming at this problem, a novel target birth intensity scheme and an improved measurement-driven scheme are incorporated into the PHD filter. The target birth intensity estimation scheme, composed of both PHD pre-filter technology and a target velocity extent method, is introduced to recursively estimate the target birth intensity by using the latest measurements at each time step. Second, based on the improved measurement-driven scheme, the measurement set at each time step is divided into the survival target measurement set, birth target measurement set, and clutter set, and meanwhile, the survival and birth target measurement sets are used to update the survival and birth targets, respectively. Lastly, a Gaussian mixture implementation of the PHD filter is presented under a linear Gaussian model assumption. The results of numerical experiments demonstrate that the proposed approach can achieve a better performance in tracking systems with an unknown newborn target intensity.

Over-step tripping often occurs in substation transformer and distribution lines. It enlarges the scope of power supply interruption and affects the reliability of power supply. This paper analyses the causes of jump tripping. Then, the zero sequence protection is set and inter-stage cooperation is improved. Finally, a novel relay protection scheme combining zero-sequence current protection and trip unit is designed. Field test shows that the scheme proposed in this paper can effectively solve the problem of over-step tripping, and avoid the expansion of power outage. It can effectively improve the reliability of power supply. The device can be widely used in intelligent distribution network and substation.

Background: SN38 (7-ethyl-10-hydroxy camptothecin), as a potent metabolite of irinotecan, is highly efficacious in cancer treatment. However, the clinical utility of SN38 has been greatly limited due to its undesirable properties, such as poor solubility and low stability. Materials and methods: In order to overcome these weaknesses, moeixitecan, a lipophilic SN38 prodrug containing a SN-38, a trolox, a succinic acid linker, and a hexadecanol chain, was loaded into liposomal nanoparticles by ethanol injection method. Results: Experiments showed that the moeixitecan-loaded liposomal nanoparticles (MLP) with a diameter of 105.10±1.49 nm have a satisfactory drug loading rate (90.54±0.41%), high solubility and stability, and showed sustained release of SN38. Notably, MLP exhibited better antitumor activity against human colon adenocarcinoma cells than irinotecan, a FDA-approved drug for the treatment of advanced colorectal cancer. Furthermore, xenograft model results showed that MLP outperformed irinotecan in terms of pharmacokinetics, in vivo therapeutic efficacy and safety. Finally, we used molecular dynamic simulations to explore the association between the structure of MLP and the physical and functional properties of MLP, moeixitecan molecules in MLP folded themselves inside the hydrocarbon chain of the lipid bilayer, which led an increased acyl chain order of the lipid bilayer, and therefore enhanced the lactone ring stability protecting it from hydrolysis. Conclusion: Our MLP constructing strategy by liposome engineering technology may serve a promising universal approach for the effective and safe delivery of lipophilic prodrug.

microRNAs (miRNAs) regulate messenger RNA (mRNA) abundance and translation during key developmental processes including muscle differentiation. Assessment of miRNA targets can provide insight into muscle biology and gene expression profiles altered by disease. mRNA and miRNA libraries were generated from C2C12 myoblasts during differentiation, and predicted miRNA targets were identified based on presence of miRNA binding sites and reciprocal expression. Seventeen miRNAs were differentially expressed at all time intervals (comparing days 0, 2, and 5) of differentiation. mRNA targets of differentially expressed miRNAs were enriched for functions related to calcium signaling and sarcomere formation. To evaluate this relationship in a disease state, we evaluated the miRNAs differentially expressed in human congenital myotonic dystrophy (CMD) myoblasts and compared with normal control. Seventy-four miRNAs were differentially expressed during healthy human myocyte maturation, of which only 12 were also up- or downregulated in CMD patient cells. The 62 miRNAs that were only differentially expressed in healthy cells were compared with differentiating C2C12 cells. Eighteen of the 62 were conserved in mouse and up- or down-regulated during mouse myoblast differentiation, and their C2C12 targets were enriched for functions related to muscle differentiation and contraction.

As one suboptimal but tractable alternative to the Bayes filter within the random finite set (RFS) framework, the probability hypothesis density (PHD) filter has attracted considerable attention because of its low computational load and ease of implementation. However, the standard PHD filter is unable to estimate the tracks of targets in clutter circumstances. Although some PHD-based trackers are proposed to estimate the tracks of targets, the track maintenance performances of these trackers suffer from significant declines in closely spaced target environments. In this paper, with the help of the track label and an association-update factor matrix, a closely spaced target track maintenance algorithm based on the Gaussian mixture PHD filter is proposed to identify and provide the trajectories of close targets over times. Numerical simulations demonstrate that the proposed algorithm is capable of correctly estimating the tracks of closely spaced targets in clutter environments, and is superior to the related multi-target trackers in terms of target states, computational load, and association accuracy of tracks.