Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize.

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

Development and Validation a UPLC-MS/MS Method for Quantification of Pentoxifylline in Beagle Plasma: Application for Pharmacokinetic Study of Food Effect.

Purpose: To develop an UPLC-MS/MS method for the quantitative analysis of pentoxifylline in beagle dog plasma and apply it to a pharmacokinetic study of food effect. Methods: Sample separation was achieved using a Kinetex Phenyl-Hexyl column (50 × 2.1 mm, 1.7 µm) with a gradient elution program in 5.5 min after a simple protein precipitation with methanol. Using the mobile phase that made up by 0.2% formic acid and 5mM ammonium formate water (A) and methanol (B). Quantitation was carried out using the positive ionization mode with multiple reaction monitoring (MRM). A randomized, single-dose, two-period crossover study was conducted in six fasted or fed beagles that received 400 mg pentoxifylline sustained-release tablets (Brand name: Shuanling™, CSPC Pharmaceutical Group). WinNonlin® software was used to calculate pharmacokinetic parameters. Results: The linear calibration range was 2-1000 ng/mL (r2> 0.99). Both intra- and inter-batch precision were less than 6.27%, and the accuracy ranged from 88.65% to 97.18%. Pentoxifylline was readily absorbed in fasted and fed dogs administered a dose of 400 mg (tmax:1.54h vs 1.83h). Compared to the fasted group, the AUC0→t and Cmax in the fed group increased by 1.71-fold and 1.30-fold, respectively. In the fasted group, the AUC0→t and Cmax values were 4684.08 h•ng/mL and 2402.33 ng/mL, respectively. In the fed group, these values were 8027.75 h•ng/mL and 3119.67 ng/mL. The difference in AUC0-t between the fed and fasted group was statistically significant. Conclusion: The novel optimized UPLC-MS/MS assay is an effective tool for the determination of pentoxifylline and has been successfully applied in pharmacokinetic studies of pentoxifylline in beagle dogs. The administration of pentoxifylline sustained-release tablets with food significantly increased the area under the time curve, and it is recommended that they should be administered during or shortly after feeding.

Integrated IBD Analysis, GWAS Analysis and Transcriptome Analysis to Identify the Candidate Genes for White Spot Disease in Maize.

Foundation parents (FPs) play an irreplaceable role in maize breeding practices. Maize white spot (MWS) is an important disease in Southwest China that always seriously reduces production. However, knowledge about the genetic mechanism of MWS resistance is limited. In this paper, a panel of 143 elite lines were collected and genotyped by using the MaizeSNP50 chip with approximately 60,000 single nucleotide polymorphisms (SNPs) and evaluated for resistance to MWS among 3 environments, and a genome-wide association study (GWAS) and transcriptome analysis were integrated to reveal the function of the identity-by-descent (IBD) segments for MWS. The results showed that (1) 225 IBD segments were identified only in the FP QB512, 192 were found only in the FP QR273 and 197 were found only in the FP HCL645. (2) The GWAS results showed that 15 common quantitative trait nucleotides (QTNs) were associated with MWS. Interestingly, SYN10137 and PZA00131.14 were in the IBD segments of QB512, and the SYN10137-PZA00131.14 region existed in more than 58% of QR273's descendants. (3) By integrating the GWAS and transcriptome analysis, Zm00001d031875 was found to located in the region of SYN10137-PZA00131.14. These results provide some new insights for the detection of MWS's genetic variation mechanisms.

Integration of GWAS, linkage analysis and transcriptome analysis to reveal the genetic basis of flowering time-related traits in maize.

Maize (Zea mays) inbred lines vary greatly in flowering time, but the genetic basis of this variation is unknown. In this study, three maize flowering-related traits (DTT, days to tasselling; DTP, days to pollen shed; DTS, days to silking) were evaluated with an association panel consisting of 226 maize inbred lines and an F2:3 population with 120 offspring from a cross between the T32 and Qi319 lines in different environments. A total of 82 significant single nucleotide polymorphisms (SNPs) and 117 candidate genes were identified by genome-wide association analysis. Twenty-one quantitative trait loci (QTLs) and 65 candidate genes were found for maize flowering time by linkage analysis with the constructed high-density genetic map. Transcriptome analysis was performed for Qi319, which is an early-maturing inbred line, and T32, which is a late-maturing inbred line, in two different environments. Compared with T32, Qi319 showed upregulation of 3815 genes and downregulation of 3906 genes. By integrating a genome-wide association study (GWAS), linkage analysis and transcriptome analysis, 25 important candidate genes for maize flowering time were identified. Together, our results provide an important resource and a foundation for an enhanced understanding of flowering time in maize.

EPA-enriched plasmalogen attenuates the cytotoxic effects of LPS-stimulated microglia on the SH-SY5Y neuronal cell line.

Microglia plays an important role in the production of inflammation in the central nervous system. Excessive nerve inflammation can cause neuronal damage and neurodegenerative disease. It has been shown that EPA-enriched ethanolamine plasmalogen (EPA-PlsEtn) significantly inhibited the expressions of inflammatory factors and suppressed neuronal loss in a rat model of Alzheimer's disease. However, whether EPA-PlsEtn protects against neuronal loss by inhibiting the activation of microglia is still not clear. Therefore, we examined the effect of PlsEtn on SH-SY5Y cells incubated by conditioned medium from LPS-induced BV2 cells as a neuroinflammation model. Results showed that pre-incubation of LPS-induced BV2 cells with PlsEtn significantly improved the viability of SH-SY5Y cells by reducing the early apoptosis. The increasing production of NO and TNF-α in BV2 cells was reversed by PlsEtn treatment, while the decreasing level of IL-10 was raised. Polarization toward M1 phenotype and activation of NLRP3 inflammasome pathways are attenuated significantly by pre-treatment of PlsEtn in LPS-induced BV2 cells. The study provides evidence for a positive effect of PlsEtn on neuroprotection and the inhibition of neuroinflammation, and PlsEtn may be explored as a potential functional ingredient with neuroprotection effects.

Correction: Xiang, Y.M.; Pan, W.F.; Jiang, H.B.; Zhu, Y.F.; Li, H. Measuring Software Modularity Based on Software Networks. Entropy 2019, 21, 344.

The authors wish to make the following corrections to the paper [...].

Dynamic Residual Dense Network for Image Denoising.

Deep convolutional neural networks have achieved great performance on various image restoration tasks. Specifically, the residual dense network (RDN) has achieved great results on image noise reduction by cascading multiple residual dense blocks (RDBs) to make full use of the hierarchical feature. However, the RDN only performs well in denoising on a single noise level, and the computational cost of the RDN increases significantly with the increase in the number of RDBs, and this only slightly improves the effect of denoising. To overcome this, we propose the dynamic residual dense network (DRDN), a dynamic network that can selectively skip some RDBs based on the noise amount of the input image. Moreover, the DRDN allows modifying the denoising strength to manually get the best outputs, which can make the network more effective for real-world denoising. Our proposed DRDN can perform better than the RDN and reduces the computational cost by 40 - 50 % . Furthermore, we surpass the state-of-the-art CBDNet by 1.34 dB on the real-world noise benchmark.

Lighting Deviation Correction for Integrating-Sphere Multispectral Imaging Systems.

In an integrating sphere multispectral imaging system, measurement inconsistency can arise when acquiring the spectral reflectances of samples. This is because the lighting condition can be changed by the measured samples, due to the multiple light reflections inside the integrating sphere. Besides, owing to non-uniform light transmission of the lens and narrow-band filters, the measured reflectance is spatially dependent. To deal with these problems, we propose a correction method that consists of two stages. The first stage employs a white board to correct non-uniformity and a small white patch to correct lighting deviation, both under the assumption of ideal Lambertian reflection. The second stage uses a polynomial regression model to further remove the lighting inconsistency when measuring non-Lambertian samples. The method is evaluated on image data acquired in a real multispectral imaging system. Experimental results illustrate that our method eliminates the measurement inconsistency considerably. This consequently improves the spectral and colorimetric accuracy in color measurement, which is crucial to practical applications.

Genetic characterization of maize germplasm derived from Suwan population and temperate resources.

BACKGROUND: The Suwan population is a well-known maize germplasm that has greatly contributed to the development of maize breeding in tropical and subtropical regions, especially in southern China. Inbred lines derived from the Suwan population always contain stronger resistance and extensive adaptability in different environments. To evaluate the genetic character of inbred lines derived from the Suwan population, a panel including 226 inbred line derived from the Suwan population and temperate resources was assembled and genotyped by using MaizeSNP50 BeadChip, which contained 56,110 genome-wide single nucleotide polymorphism (SNP) markers. This panel contained 98 temperate inbred line and 128 lines derived from the Suwan population. RESULTS: The results showed that high genetic diversity was found, with PIC and GD to be 0.67 and 0.60, respectively. In addition, two novel subgroups were identified, with representative inbred lines as HCL645 and Ki32, respectively. One acknowledged heterotic group of Iowa Stiff Stalk Synthetic (SS) was also identified in this study. This study can provide some additional scientific evidence for heterotic group division and use in maize. Additionally, lower linkage disequilibrium (LD) levels and weaker genetic relationships were found, with an average LD level of 41.15 kb that varied from 3.5 to 96 kb. A total of 82.8% of paired relative kinships ranged from 0.05 to 0.28. CONCLUSIONS: These results would not only facilitate maize breeding practices in tropical and subtropical regions, but also revealed that this panel can be used in dissecting the genetic basis of complex quantitative traits' variations by using genome-wide association studies (GWAS).

Measuring Software Modularity Based on Software Networks.

Modularity has been regarded as one of the most important properties of a successful software design. It has significant impact on many external quality attributes such as reusability, maintainability, and understandability. Thus, proposing metrics to measure the software modularity can be very useful. Although several metrics have been proposed to characterize some modularity-related attributes, they fail to characterize software modularity as a whole. A complex network uses network models to abstract the internal structure of complex systems, providing a general way to analyze complex systems as a whole. In this paper, we introduce the complex network theory into software engineering and employ modularity, a metric widely used in the field of community detection in complex network research, to measure software modularity as a whole. First, a specific piece of software is represented by a software network, feature coupling network (FCN), where methods and attributes are nodes, couplings between methods and attributes are edges, and the weight on the edges denotes the coupling strength. Then, modularity is applied to the FCN to measure software modularity. We apply the Weyuker's criteria which is widely used in the field of software metrics, to validate the modularity as a software metric theoretically, and also perform an empirical evaluation using open-source Java software systems to show its effectiveness as a software metric to measure software modularity.

Camera lens radial distortion correction using two-view projective invariants.

This Letter proposes a new method for automatically removing radial lens distortion from image feature point correspondences of two views. Based on the projective geometric relationship between two views of a planar scene, we have derived a system of algebraic equations that relates the invariants to the distortion parameters to be found. We then propose a noniterative procedure to solve the equations system, and a kernel-voting scheme to select the best root. Being a noniterative approach, our method overcomes many problems with the conventional iterative approach. It also largely decouples the estimation of the distortion from the estimation of other camera parameters and, therefore, delivers more reliable results. Experiments on both synthetic data and real images have provided satisfactory results.

Seeker optimization algorithm for parameter estimation of time-delay chaotic systems.

Time-delay chaotic systems have some very interesting properties, and their parameter estimation has received increasing interest in the recent years. It is well known that parameter estimation of a chaotic system is a nonlinear, multivariable, and multimodal optimization problem for which global optimization techniques are required in order to avoid local minima. In this work, a seeker-optimization-algorithm (SOA)-based method is proposed to address this issue. In the SOA, search direction is based on the empirical gradients by evaluating the response to the position changes, and step length is based on uncertainty reasoning by using a simple fuzzy rule. The performance of the algorithm is evaluated on two typical test systems. Moreover, two state-of-the-art algorithms (i.e., particle swarm optimization and differential evolution) are also considered for comparison. The simulation results show that the proposed algorithm is better than or at least as good as the other two algorithms and can effectively solve the parameter estimation problem of time-delay chaotic systems.