Electrical modulation properties of DNA drug molecules.

DNA drug molecules are not only widely used in gene therapy, but also play an important role in controlling the electrical properties of molecular electronics. Covalent binding, groove binding and intercalation are all important forms of drug-DNA interaction. But its applications are limited due to a lack of understanding of the electron transport mechanisms after different drug-DNA interaction modes. Here, we used a combination of density functional theory calculations and nonequilibrium Green's function formulation with decoherence to study the effect of drug molecules on the charge transport property of DNA under three different binding modes. Conductance of DNA is found to decrease from 2.35E-5 G0 to 1.95E-6 G0 upon doxorubicin intercalation due to modifications of the density of states in the near-highest occupied molecular orbital region, δG = 1105.13%. Additionally, the conductance of DNA after cis-[Pt(NH3)2(py)Cl]+ covalent binding increases from 1.02E-6 G0 to 5.25E-5 G0, δG = 5047.06%. However, in the case of pentamidine groove binding, because there is no direct change in DNA molecular structure during drug binding, the conductance changes before and after drug binding is much smaller than in the two above cases, δG = 90.43%. Our theoretical calculations suggest that the conductance of DNA can be regulated by different drug molecules or switching the interaction modes between small molecules and DNA. This regulation opens new possibilities for their potential applications in controllable modulation of the electron transport property of DNA.

Nitrogen-Doped Carbon Dots Enhanced Hydrogen Carbonate-Hydrogen Peroxide Chemiluminescent Reaction and its Application in Ascorbic Acid Sensing.

Nitrogen-doped carbon dots (N-CDs) were prepared by self-exothermic procedure using grasshopper powder as a single precursor. The prepared N-CDs not only have excellent fluorescence properties, but also can catalyze and enhance the ultra-weak chemiluminescence of NaHCO3-H2O2. The reaction conditions of NaHCO3-H2O2-N-CDs CL were optimized. Under the optimal experimental conditions, when AA was added to the NaHCO3-H2O2-N-CDs CL system, AA had a significant inhibitory effect on the CL intensity of NaHCO3-H2O2-N-CDs. There was a good linear relationship between the calculated lg(I0/I) and the concentration of AA (C), and the calibration curve equation was lg(I0/I) = 0.03667 C-0.00708 (µM). The established CL analysis method has a detection limit of 0.12 µM for AA and a linear range of 0-50 µM. The selectivity of CL method was evaluated, and the method was successfully applied to the determination of AA in vegetable and fruit samples. The spiked recoveries were between 88.9% and 118.9%, which indicated that the method was simple, rapid, and sensitive, and had great potential in the determination of AA in foods.

Hydrophilic interaction chromatographic evaluation of zwitterionic polymer grafted silica gel via multiple binding sites.

A novel zwitterionic polymer grafted silica stationary phase, Sil-PZIC, was prepared by bonding poly(ethylene maleic anhydride) molecules on the surface of silica via multiple binding sites, followed by ammonolysis of maleic anhydride through a nucleophilic substitution reaction with ethylenediamine. The stationary phase was characterized by solid-state 13C nuclear magnetic resonance, zeta potential, and elemental analysis and the results show the successful encapsulation of zwitterionic polymer on the surface of silica. The chromatographic performance of Sil-PZIC was investigated by using nucleosides and nucleic bases as test analytes The variation of retention and separation performance of these model compounds were investigated by varying the chromatographic conditions such as the components of mobile phase, salt concentration, and pH. The results show that the retention of the Sil-PZIC phase was dominated by a hydrophilic partitioning mechanism accompanied by secondary interactions such as electrostatic and hydrogen bonding. In addition, saccharides and Amadori compounds were also well separated on the Sil-PZIC, indicating that the Sil-PZIC column has potential application for separation of the polar compound.

Dissolved trace elements in the Ganges-Brahmaputra-Meghna River Basin: A new approach for estimating trace element flux inputs from rivers into the world's oceans.

Understanding the changes in the chemical compositions of dissolved trace elements from source to sink is important for determining their spatiotemporal variations and the contributions from each sub-catchment in the Ganges, Brahmaputra, and Meghna Rivers. To estimate weathering and matter transfer in these Rivers and the Ganges-Brahmaputra-Meghna (G-B-M) Estuary, we measured 15 dissolved trace element concentrations from surface and bottom water samples and exchangeable trace metals from suspended particulate matter (SPM). From December 2019 to January 2020, post-monsoon samples were collected from the upstream of the three rivers and the G-B-M Estuary. Dissolved trace elements in the Ganges and Meghna Rivers exhibited remarkable spatial variations, whereas those in the Brahmaputra River and the G-B-M Estuary were uniform. The dissolved trace elements, basic information (river length and drainage area), and physicochemical parameters (pH, dissolved oxygen, and conductivity) of the three rivers were inconsistent. The sample sites near urban areas and industrial centers had high concentrations of dissolved trace elements. In the G-B-M Estuary, iron and lead concentrations decreased along the salinity gradient, whereas selenium levels gradually increased, which may have been released by the SPM owing to its highly exchangeable trace metals. Compared with historical concentrations, trace elements that entered the G-B Estuary from the Ganges and Brahmaputra Rivers exhibited either decreased or increased metal fluxes due to additional terrigenous sources, suggesting that the inputs of trace element flux from the Ganges and Brahmaputra Rivers into the oceans may need to be re-evaluated. Furthermore, Fe and Pb concentrations and river fluxes in the Ganges and Changjiang have decreased in recent years. Hence, the fluxes of certain trace elements that enter the oceans from large rivers may require re-evaluation.

A novel microRNA, novel-m009C, regulates methamphetamine rewarding effects.

Methamphetamine (METH) is a widely abused psychostimulant, whose hyper-rewarding property is believed to underlie its addictive effect, but the molecular mechanism regulating this effect remains unclear. We previously reported that decreased expression of a novel microRNA (miRNA), novel-m009C, is implicated in the regulation of METH hyperlocomotion. Here, we found that novel-m009C may be homologous to hsa-miR-604. Its expression is consistently downregulated in the nucleus accumbens (NAc) of mice when exposed to METH and cocaine, whereas significant alterations in novel-m009C expression were not observed in the NAc of mice subjected to other rewarding and psychiatric stimuli, such as sucrose, morphine and MK-801. We further found the substantial reduction in novel-m009C expression may be regulated by both dopamine receptor D1 (D1R) and D2 (D2R). Increasing novel-m009C levels in the NAc attenuated METH-induced conditioned place preference (CPP) and hyperlocomotion, whereas inhibiting novel-m009C expression in the NAc enhanced these effects but did not change the preference of mice for a natural reward, i.e., sucrose. These effects may involve targeting of genes important for the synaptic transmission, such as Grin1 (NMDAR subunit 1). Our findings demonstrate an important role for NAc novel-m009C in regulating METH reward, reveal a novel molecular regulator of the actions of METH on brain reward circuitries and provide a new strategy for treating METH addiction based on the modulation of small non-coding RNAs.

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks.

The IEEE 802.11 standard provides multi-rate support for different versions. As there is no specification on the dynamic strategy to adjust the rate, different rate adaptation algorithms are applied according to different manufacturers. Therefore, it is often hard to interpret the performance discrepancy of various devices. Moreover, the ever-changing channels always challenge the rate adaptation, especially in the scenario with scarce spectrum and low SNR. As a result, it is important to sense the radio environment cognitively and reduce the unnecessary oscillation of the transmission rate. In this paper, we propose an environment-aware robust (EAR) algorithm. This algorithm employs an occasional small packet, designs a rate scheme adaptive to the environment, and enhances the robustness. We verify the throughput of EAR using network simulator NS-3 in terms of station number, motion speed and node distance. We also compare the proposed algorithm with three benchmark methods: AARF, RBAR and CHARM. Simulation results demonstrate that EAR outperforms other algorithms in several wireless environments, greatly improving the system robustness and throughput.

A triple-diazonium reagent for virus crosslinking and the synthesis of an azo-linked molecular cage.

The first bench-stable triple-diazonium reagent (TDA-1) was rationally designed and synthesized for coupling and crosslinking. The three reactive sites of TDA-1 can react with phenol-containing molecules as well as plant viruses in aqueous buffers efficiently. In addition, a new-type azo-linked cage was constructed by the direct reaction of TDA-1 with a triple-phenol molecule and was characterized by X-ray crystallography.

Gram-scale synthesis of nitrogen-doped carbon dots from locusts for selective determination of sunset yellow in food samples.

Locust powder was converted into water-soluble fluorescent nitrogen-doped carbon dots (N-CDs) with gram-scale yield through a self-exothermic reaction between nitric acid and diethylenetriamine (DETA) within 10 min. The morphology, elemental information, and optical properties of the N-CDs were characterized using high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy, and Fourier-transform infrared, ultraviolet-visible and fluorescence spectroscopy. Spectroscopic investigation indicated that the fluorescence emission behaviour of N-CDs is excitation wavelength dependent, with the strongest emission peak at 470 nm using a 390 nm excitation wavelength. The strong absorption peak of sunset yellow (SY) at 482 nm overlaps substantially with the blue emission peak (470 nm) of N-CDs. This enables the fluorescence emission of N-CDs to be obviously quenched by SY through the inner filter effect. There was a good linear relationship between the fluorescence quenching degree and the concentrations of SY within the range 0.5-40 µM. The detection limit of developed fluorescence assay for SY is 28 nM, and the relative standard deviation is 2.3% (c = 10 µM). The N-CDs derived from locusts by the self-exothermic reaction are highly selective and sensitive fluorescent probes for SY, which were applied to the fluorescence sensing of SY in different food samples with satisfactory results.

Electronic characteristics of BRCA1 mutations in DNA.

The efficient and low-cost way for gene mutation detection and identification are conducive for the detection of disease. Here, we report the electronic characteristics of the gene of breast cancer 1 in four common mutation types: duplication, single nucleotide variant, deletion, and indel. The electronic characteristics are investigated by the combination of density functional theory and non-equilibrium Green's function formulation with decoherence. The magnitude of conductance of these DNA molecules and mutational changes are found to be detectable experimentally. In this study, we also find the significant mutation type dependent on the change of conductance. Hence these mutations are expected to be identifiable. We find deletion type mutation shows the largest change in relative conductance (~97%), whereas the indel mutation shows the smallest change in relative conductance (~27%). Therefore, this work presents a possibility of electronic detection and identification of mutations in DNA, which could be an efficient method as compared to the conventional methods.

Effect of cytosine hydroxymethylation on DNA charge transport.

DNA hydroxymethylation plays a very important role in some biological processes, such as DNA methylation process. In addition, its presence can also cause some diseases. In this paper, the electrical properties of cytosine hydroxymethylated (Chm) DNA sequences are studied. The density functional theory (DFT) and Landauer-Büttiker framework are used to study the decoherence conductance and transmission of the Chm strands in different configurations, which provides a theoretical basis for the detection of Chm. The results show that the conductance of the hydroxymethylated DNA strand is smaller than that of the native and methylated strands. The length dependence of the Chm strands is also studied. With the length increasing, the conductance becomes larger. This study shows that DNA methylation can be detected electrically.

An Information Theory Inspired Real-Time Self-Adaptive Scheduling for Production-Logistics Resources: Framework, Principle, and Implementation.

The development of industrial-enabling technology, such as the industrial Internet of Things and physical network system, makes it possible to use real-time information in production-logistics scheduling. Real-time information in an intelligent factory is random, such as the arrival of customers' jobs, and fuzzy, such as the processing time of Production-Logistics Resources. Besides, the coordination of production and logistic resources in a flexible workshop is also a hot issue. The availability of this information will enhance the quality of making scheduling decisions. However, when and how to use this information to realize the adaptive collaboration of Production-Logistics Resources are vital issues. Therefore, this paper studies the above problems by establishing a real-time reaction scheduling framework of Production-Logistics Resources dynamic cooperation. Firstly, a real-time task triggering strategy to maximize information utilization is proposed to explore when to use real-time information. Secondly, a collaborative method for Production-Logistics Resources is studied to explore how to use real-time information. Thirdly, a real-time self-adaptive scheduling algorithm based on information entropy is utilized to obtain a stable and feasible solution. Finally, the effectiveness and advancement of the proposed method are verified by a practical case.

Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory.

In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in the factory, such as the industrial Internet of things (IIoT) and cloud manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with a random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

Entropy Based Data Expansion Method for Blind Image Quality Assessment.

Image quality assessment (IQA) is a fundamental technology for image applications that can help correct low-quality images during the capture process. The ability to expand distorted images and create human visual system (HVS)-aware labels for training is the key to performing IQA tasks using deep neural networks (DNNs), and image quality is highly sensitive to changes in entropy. Therefore, a new data expansion method based on entropy and guided by saliency and distortion is proposed in this paper. We introduce saliency into a large-scale expansion strategy for the first time. We regionally add distortion to a set of original images to obtain a distorted image database and label the distorted images using entropy. The careful design of the distorted images and the entropy-based labels fully reflects the influences of both saliency and distortion on quality. The expanded database plays an important role in the application of a DNN for IQA. Experimental results on IQA databases demonstrate the effectiveness of the expansion method, and the network's prediction effect on the IQA databases is found to be improved compared with its predecessor algorithm. Therefore, we conclude that a data expansion approach that fully reflects HVS-aware quality factors is beneficial for IQA. This study presents a novel method for incorporating saliency into IQA, namely, representing it as regional distortion.

3D thickness distributions of plano lenses as a means of cavity pressure characterization in microinjection molding.

This work presents a novel nondestructive cavity pressure characterization approach in microinjection molding (µIM) through measuring 3D part thickness distributions. For this purpose, a plano lens was designed and experiments based on Taguchi method were conducted. Both overall and local lens thickness distributions under various process conditions were analyzed in terms of their relevance with the cavity pressure during molding. Unexpectedly, a reliable linear regression model was developed fulfilling nondestructive multi-point or even continuous cavity pressure characterization with the overall lens thickness distribution. Furthermore, the topography of the constructed 3D thickness surface was found to depend on both process condition and measuring position. Finally, the process conditions were optimized for obtaining uniform distributions of both 3D thickness and cavity pressure.

Synthesis of cobalt-based magnetic nanoporous carbon core-shell molecularly imprinted polymers for the solid-phase extraction of phthalate plasticizers in edible oil.

In this work, cobalt magnetic nanoporous carbon (Co-MNPC) is employed as an alternative to intensively used Fe3O4 cores for the preparation of magnetic molecularly imprinted polymers (Co-MNPC@MIPs) for the first time. Co-MNPC was prepared by one-step carbonization of Zeolitic Imidazolate Framework-67 (ZIF-67). Compared with the traditional Fe3O4 core, Co-MNPC showed a high specific surface area and large pore volumes. The prepared adsorbents, which could be rapidly collected from a matrix by external magnetic field, were applied for solid-phase extraction of phthalate plasticizers in edible oil. Several requisite extraction parameters were optimized to achieve desired extraction performance. Under the optimum extraction conditions, Co-MNPC@MIPs displayed better performance than commercialized columns. An analysis method based on Co-MNPC@MIPs coupled with gas chromatography (GC) was established. The linear range was 1-150 µg mL-1, and the detection limit range was 0.010-0.025 µg mL-1. The spiked recovery rate of the five phthalate plasticizers was 81.6-102.2%, with a relative standard deviation of 3.25-12.02%. Finally, the proposed method showed good feasibility for phthalate plasticizer extraction from edible oil.

Matrine-Type Alkaloids from the Roots of Sophora flavescens and Their Antiviral Activities against the Hepatitis B Virus.

Eight new matrine-type alkaloids, flavesines G-J (1-4), alopecurine B (5), 7,11-dehydro-oxymatrine (6), 10-oxy-5,6-dehydromatrine (7), and 10-oxysophoridine (8), along with nine known analogues (9-17) were isolated from the roots of Sophora flavescens. Compounds 1-3 are the first natural matrine-type alkaloids with an open-loop ring D, while compound 4 represents an unprecedented dimerization pattern constructed from matrine and piperidine, and 5 is the first example of a matrine-type alkaloid with cleavage of the C-5-C-6 bond. The new structures were elucidated by means of spectroscopic data analysis (including NMR, MS, IR, and UV), and the absolute configurations were determined using single-crystal X-ray diffraction and ECD data. The isolated alkaloids were evaluated for their antiviral activity against hepatitis B virus, and compounds 1, 4, 5, 10, and 14 exhibited comparable antiviral potencies to matrine.

Investigation of the chromatographic regulation properties of benzyl groups attached to bridging nitrogen atoms in a calixtriazine-bonded stationary phase.

Two reversed-phase/anion-exchange mixed-mode stationary phases for high-performance liquid chromatography using calixtriazines as chromatographic ligands were investigated with Tanaka test solutes, monosubstituted benzenes, aromatic positional isomers, and inorganic anions. Calixtriazine as a chromatographic ligand has been reported previously, but the benzylated nitrogen-bridged calixtriazine-bonded silica gel reported in this study is new. The experimental data showed that the calixtriazine platform is a unique chromatographic selector because its multiple active sites are available for different solutes and its chromatographic selectivity could be tuned by introducing substituent on the bridging nitrogen atoms present in the calixtriazine matrix. The synergistic effects of aromatic rings, nitrogen atoms, benzyl groups, and tunable cavity in the host molecule influenced the separation selectivity by multiple retention mechanisms. Such hybrid stationary phases provide more versatility and have great potential in the analysis of complex samples. Moreover, the synthetic protocols presented herein may provide an alternative understanding on macrocyclic host-guest chemistry, leading to new and selective separation media.

Solid-phase extraction of aflatoxins using a nanosorbent consisting of a magnetized nanoporous carbon core coated with a molecularly imprinted polymer.

A core consisting of nanoporous carbon (MNPC) and magnetized with Co3O4 was coated with a molecularly imprinted polymer (MIP) by atom transfer radical precipitation polymerization. Ethyl 3-coumarincarboxylate was used as a pseudo-template to give a MIP that has a fairly specific recognition capability for aflatoxins. Batch rebinding studies were carried out to determine the specific adsorption equilibrium and specific recognition. Extraction is achieved in a single step by mixing and vortexing the sample extract with the Co-MNPC@MIP. The loaded nanosorbent was then magnetically separated and eluted with acetonitrile/water (6/4, v/v). The aflatoxins were then quantified by HPLC. Under optimal conditions, the detection limits for aflatoxins typically are 0.05-0.07 ng mL-1, recoveries from spiked corn are found to be 75.1 to 99.4%, and relative standard deviations range from 1.7 to 5.1 (n = 6). Graphical abstract Poly(methacrylic acid) was imprinted with the pseudo-template ethyl 3-coumarincarboxylate by atom transfer radical precipitation polymerization on the surface of cobalt-derived magnetic nanoporous carbon (Co-MNPC). This nanosorbent was used for the magnetic solid phase extraction of aflatoxins, followed by HPLC analysis.

Joint Source and Channel Rate Allocation over Noisy Channels in a Vehicle Tracking Multimedia Internet of Things System.

As an emerging type of Internet of Things (IoT), multimedia IoT (MIoT) has been widely used in the domains of healthcare, smart buildings/homes, transportation and surveillance. In the mobile surveillance system for vehicle tracking, multiple mobile camera nodes capture and upload videos to a cloud server to track the target. Due to the random distribution and mobility of camera nodes, wireless networks are chosen for video transmission. However, the tracking precision can be decreased because of degradation of video quality caused by limited wireless transmission resources and transmission errors. In this paper, we propose a joint source and channel rate allocation scheme to optimize the performance of vehicle tracking in cloud servers. The proposed scheme considers the video content features that impact tracking precision for optimal rate allocation. To improve the reliability of data transmission and the real-time video communication, forward error correction is adopted in the application layer. Extensive experiments are conducted on videos from the Object Tracking Benchmark using the H.264/AVC standard and a kernelized correlation filter tracking scheme. The results show that the proposed scheme can allocate rates efficiently and provide high quality tracking service under the total transmission rate constraints.

Robust Object Tracking Based on Motion Consistency.

Object tracking is an important research direction in computer vision and is widely used in video surveillance, security monitoring, video analysis and other fields. Conventional tracking algorithms perform poorly in specific scenes, such as a target with fast motion and occlusion. The candidate samples may lose the true target due to its fast motion. Moreover, the appearance of the target may change with movement. In this paper, we propose an object tracking algorithm based on motion consistency. In the state transition model, candidate samples are obtained by the target state, which is predicted according to the temporal correlation. In the appearance model, we define the position factor to represent the different importance of candidate samples in different positions using the double Gaussian probability model. The candidate sample with highest likelihood is selected as the tracking result by combining the holistic and local responses with the position factor. Moreover, an adaptive template updating scheme is proposed to adapt to the target's appearance changes, especially those caused by fast motion. The experimental results on a 2013 benchmark dataset demonstrate that the proposed algorithm performs better in scenes with fast motion and partial or full occlusion compared to the state-of-the-art algorithms.