Genome-wide association study reveals that GhTRL1 and GhPIN8 affect cotton root development.

KEY MESSAGE: Two regions located at chromosome A05 and D04 were found to be significantly associated with 0-0.5 mm and 0.5-2 mm diameter roots, respectively, and two candidate genes related to root development were identified. Roots absorb water and nutrients, and play an important role in plant growth. However, there are few genetic developmental studies on cotton root structural traits. In this study, we used 200 upland cotton (Gossypium hirsutum L.) varieties to analyze the phenotypic variation of 43 traits. A total of 2001 related single-nucleotide polymorphism (SNP) sites located within or near 1046 genes were detected through a genome-wide association study (GWAS). The 32 root traits were linked to SNPs that corresponded to 317 nonrepetitive genes. For SNPs associated with root length and 0-0.5 mm diameter root traits, a significant peak appeared on chromosome A05 (between 21.91 and 22.24 Mb). For SNPs associated with root surface area, root volume and 0.5-2 mm diameter root traits, a significant peak appeared on chromosome D04 (between 7.35 and 7.70 Mb). Within these two key regions, SNPs were detected in the promoter and coding regions of two candidate genes, GhTRL1-A05 and GhPIN8-D04. The expression levels of these two genes also changed significantly according to transcriptome sequencing and quantitative real-time PCR (qRT-PCR). After silencing the GhTRL1 and GhPIN8 genes via virus-induced gene silencing (VIGS), we found that the plants expressing TRV2::GhTRL1 and TRV2::GhPIN8 had a reduced root length, surface area. Moreover, the contents of cis-12-oxo-phytodienoic acid (cis-OPDA), isopentenyl adenosine (iPR) and cis-zeatin (cZ) in the roots of the plants expressing TRV2::GhTRL1 decreased. This study contributes to the cultivation and improvement of cotton varieties.

Effective Chiral Discrimination of Amino Acids through Oligosaccharide Incorporation by Trapped Ion Mobility Spectrometry.

Chiral analysis is critical to many research fields due to different biological functions of enantiomers in living systems. Although the use of ion mobility spectrometry (IMS) has become an alternative technology in the area of chiral measurements, there is still a lack of a general chiral selector for IMS-based chiral recognition, especially for small chiral molecules. Here, a new method using oligosaccharides as the chiral selector has been developed to discriminate chiral amino acids (AAs) by trapped ion mobility spectrometry-mass spectrometry (TIMS-MS). We analyzed 21 chiral amino acids, including small molecules (e.g., alanine and cysteine). Our data showed that the use of nonreducing tetrasaccharides was effective for the separation of chiral AAs, which differentiated 21 chiral AAs without using metal ions. By further incorporating a copper ion, the separation resolution could be improved to 1.64 on average, which accounts for an additional 52% improvement on top of the already achieved separation in metal-free analysis. These results indicate that the use of tetrasaccharides is an effective strategy for the separation of AA enantiomers by TIMS. The method developed in this study may open up a new strategy for effective IMS-based chiral analysis.

Resolution enhancement of overlapping peaks of ion mobility spectrometry based on improved particle swarm optimization algorithm.

RATIONALE: Ion mobility spectrometry (IMS) is a powerful analytical tool that has been widely applied in many fields. However, the limited structural resolution of IMS results in peak overlapping in the analysis of samples with similar structures. We propose a novel method, improved particle swarm optimization (IPSO), for the separation of IMS overlapping peaks. METHODS: This method, which prevents local optimization, is used to identify the peak model coefficients of IMS. Moreover, we use the half-peak width characteristics of IMS to determine the particle position range, which eliminates impossible combinations of single peaks and reduces the difficulty of identification of coefficients. RESULTS: During a comparison in performance between IPSO and the genetic algorithm (GA), the results show that the maximum separation error of IPSO is only 1.45%, while the error of the GA is up to 17.43%. Moreover, the time consumed by IPSO is 95% less than that of the GA, and IPSO has a greater robustness under the same separation error conditions. CONCLUSIONS: The method proposed provides accurate analytical results in separating overlapping IMS peaks even in cases of severe overlaps, which greatly enhances the structural resolution of IMS.

A game theoretical model for location of terror response facilities under capacitated resources.

This paper is concerned with the effect of capacity constraints on the locations of terror response facilities. We assume that the state has limited resources, and multiple facilities may be involved in the response until the demand is satisfied consequently. We formulate a leader-follower game model between the state and the terrorist and prove the existence and uniqueness of the Nash equilibrium. An integer linear programming is proposed to obtain the equilibrium results when the facility number is fixed. The problem is demonstrated by a case study of the 19 districts of Shanghai, China.

Patriotism, nationalism, and evaluations of the government's handling of the coronavirus crisis.

Introduction: The COVID-19 pandemic has been accompanied by a global rise of nationalism, and many countries' responses to the pandemic have further intensified nationalist sentiments. The public is polarized over government policies toward the pandemic. Hence, this study examined the associations of patriotism and nationalism with the support for lockdown policies and evaluations of governmental performance. Methods: We recruited 180 participants from one Chinese university. Results: Patriotism and nationalism had a direct effect on evaluations of governmental performance. Patriotism also had indirect effects on favorable evaluations of governmental performance through the support of lockdown policies. In addition, this study examined the relationship of threat perception and evaluations of governmental performance in the pandemic. Discussion: This relationship was found to be insignificant; however, the interaction effects between threat perception and patriotism on evaluations of governmental performance were significant. The implications of the study results are discussed.

GhMYB102 promotes drought resistance by regulating drought-responsive genes and ABA biosynthesis in cotton (Gossypium hirsutum L.).

The MYB transcription factor (TF) family is among the largest TF families and plays an important role in plant growth and stress response. However, few studies have investigated the role of the MYB gene in drought resistance in cotton. In this study, we analysed the drought transcriptomic data of cotton and identified that the GhMYB102 gene was significantly upregulated in upland cotton during the early stages of drought stress. Bioinformatics analysis showed that the amino acid sequence encoded by GhMYB102 contained two highly conserved MYB binding domains belonging to R2R3-MYB TFs. GhMYB102 was most closely related to AtMYB102. GhMYB102 is mainly expressed in roots and is induced by abiotic stresses and abscisic acid (ABA); it is localised in the nucleus and has transcriptional activation activity. Silencing of GhMYB102 decreased plant drought resistance. In addition, dual-luciferase assays and yeast single hybridisation analysis showed that GhMYB102 could directly bind the MYB motif elements in the promoter regions of GhNCED1 and GhZAT10. These results indicate that GhMYB102 plays a positive role in drought tolerance by regulating the expression of GhNCED1 and GhZAT10. Thus, GhMYB102 enhances drought resistance by participating in ABA biosynthesis or regulating the expression of drought-responsive genes.

A Large-Scale Multiobjective Particle Swarm Optimizer With Enhanced Balance of Convergence and Diversity.

Large-scale multiobjective optimization problems (LSMOPs) continue to be challenging for existing multiobjective evolutionary algorithms (MOEAs). The main difficulties are that: 1) the diversity preservation in both the objective space and the decision space needs to be taken into account when solving LSMOPs and 2) the existing learning structures in current MOEAs usually make the learning operators only coincidentally serve convergence and diversity, leading to difficulties in balancing these two factors. Therefore, balancing convergence and diversity in current MOEAs is difficult. To address these issues, this article proposes a multiobjective particle swarm optimizer with enhanced balance of convergence and diversity (MPSO-EBCD). In MPSO-EBCD, a novel velocity update structure for multiobjective particle swarm optimization is put forward, dividing the convergence, and diversity preservation operations into independent components. Following the proposed update structure, a weighted convergence factor is introduced to serve the convergence strategy, whilst a diversity preservation strategy is built to uniformly distribute the particles in the searched space based on a proposed multidimensional local sparseness degree indicator. By this means, MPSO-EBCD is able to balance convergence and diversity with specific parameters in independent operators. Experimental results on LSMOP benchmarks and a voltage transformer optimization problem demonstrate the competitiveness of the proposed algorithm compared to several state-of-the-art MOEAs.

Skeletal Muscle Mass Measurement Using Cone-Beam Computed Tomography in Patients With Head and Neck Cancer.

Background and purpose: Head and neck cancer (HNC) patients usually present with malnutrition during radiotherapy, leading to loss of skeletal muscle mass (SMM) and poor clinical outcomes. CT has been used in clinical practice for measuring SMM in cancer patients. However, its clinical application for monitoring SMM is limited by the expensive price and high radiation exposure. This study aimed to investigate the feasibility of cone-beam computed tomography (CBCT) for assessing SMM and its changes in HNC patients undergoing radiotherapy. Materials and methods: This study was divided into two parts. In part 1 (n = 32), the cross-sectional of skeletal muscle area (SMA) at the third cervical vertebra (C3) based on CBCT and computed tomography (CT) was assessed. In part 2 (n = 30), CT and CBCT were performed, and patients' weight was measured before and at four different time points during radiotherapy. SMAs at C3 were independently identified by three senior radiation oncologists. The interobserver agreement of SMA on CBCT (SMACBCT) findings was analyzed using the intraclass correlation coefficient (ICC). One-way analysis of variance was used to evaluate the interobserver variability and statistical significance for SMA measurements. CBCT and CT measurement differences and correlations were analyzed using paired sample t-test and Pearson correlation analysis, respectively. The Krouwer variant of the Bland-Altman plot was used to analyze the agreement of SMA measurements between CBCT and CT. A simple linear regression model was used to analyze the relationship of SMA measurements between the two imaging techniques, and the equation was established. A repeated-measures ANOVA was performed to evaluate the effects and interactions between weight loss, SMA loss, and time. Results: SMACBCT demonstrated excellent interobserver reliability; no significant difference between SMACBCT and SMA on CT (SMACT) at C3 was observed in all patients. The SMACBCT and SMACT were highly correlated (r = 0.966; 95% confidence interval = 0.955-0.975; p < 0.001). Bland-Altman analysis revealed that SMACBCT was generally higher than SMACT. The predicted SMA value at C3 on CT using CBCT was similar to the actual value. Moreover, significant differences between SMA and weight loss (F =10.99, p = 0.002), groups (weight loss and SMA loss) and times (4 time points) (F = 3.93, p = 0.013), and mean percent loss over time (F = 7.618, p < 0.001) were noted. Conclusion: CBCT may be used as an alternative for CT to measure SMA in HNC patients during radiotherapy.

Effective separation of carbohydrate isomers using metal cation and halogen anion complexes in trapped ion mobility spectrometry.

Comprehensive analysis of carbohydrates, one of the critical steps towards the fundamental understanding of biological systems, has been hindered by the identifications of their complex isomeric structures differing in monosaccharide constituents, linkage positions, and configurations. While ion mobility spectrometry-mass spectrometry (IMS-MS) based methods have shown their utilities in performing glycomics measurements, there is still a lack of analytical methods allowing effective isomeric carbohydrate separation. Here, we systematically investigated the effect of alkaline earth cations (Ca2+ and Ba2+) and halogen anions (Cl-, Br- and I-) addition on the separation of 21 pairs of isomeric oligosaccharides using trapped ion mobility spectrometry-mass spectrometry (TIMS-MS). [M + Ca + I]+ complex (M is an oligosaccharide) has shown experimentally to be the optimum complex for the separation of all 21 pairs of isomeric oligosaccharides used in this study with a calculated average resolution (r) ~ 1.82 and resolving power (R) ~ 100-150. The separation capability of this complex was further demonstrated by using mixtures of 15 oligosaccharides. The optimum [M + Ca + I]+ complex can be potentially used as an effective complex for enhancing the IMS separation resolution of isomeric carbohydrates.

Medical adhesive vs hookwire for computed tomography-guided preoperative localization and risk factors of major complications.

OBJECTIVE: To compare the efficacy of medical adhesive and hookwire as CT-guided non-palpable pulmonary nodule (NPN) localization methods before video-assisted thoracoscopic surgery (VATS) resection, and determine the risk factors for common complications during localization. METHODS: This was a single-center non-randomized retrospective study. 102 consecutive patients with 109 NPNs were divided into Group A (medical adhesive, 66 patients, 72 nodules) and Group B (hookwire, 36 patients, 37 nodules) before VATS. Patient- and nodule-based characteristics were compared. Logistic regression was performed to identify the risk factors for complications. RESULTS: Localization was successfully performed in all the NPNs. For Group A, the rate of pneumothorax immediately after localization was lower (p = 0.049) and the localization-to-surgery interval was longer (p = 0.011) than Group B. There was no significant difference in rates of hemorrhage after needle withdrawal between the two groups (p = 0.198). Hookwire ( vs medical adhesive) (ß = 1.12, p = 0.018), total insertion depth (ß = -0.41, p = 0.013), pleura-needle angle (ß = -0.04, p = 0.025) and grade of hemorrhage after needle withdrawal (ß = -0.96, p = 0.030) were independently associated with pneumothorax, while age (ß = -0.94, p = 0.018), tumor size (ß = 0.29, p = 0.007) and its distance from the pleural surface (ß = 0.14, p = 0.004) were associated with higher grade hemorrhage after needle withdrawal. CONCLUSION: Compared with hookwire, localization with medical adhesive excelled in lower risk of pneumothorax, a more flexible localization-to-surgery interval, and had similar rates of hemorrhage after needle withdrawal. Hookwire is an independent risk factor of pneumothorax immediately after localization. ADVANCES IN KNOWLEDGE: This study added new clinical evidence to the efficacy of medical adhesive in pre-operative CT-guided NPN localization.

Improving glycan isomeric separation via metal ion incorporation for drift tube ion mobility-mass spectrometry.

Glycosylated proteins are an essential class of molecules playing critical roles in complex biological systems. Understanding their biological functions remains extremely difficult due to the extremely broad compositions and structure variations of glycans. Although the combination of ion mobility spectrometry and mass spectrometry (IMS-MS) has become a promising technique in glycan structure characterization and composition identification, the insufficient resolving power of most IMS-MS instruments has limited its utility in performing the comprehensive structure characterization of glycans. To mitigate the low IMS resolving power, metal ion incorporation has been employed to enhance the separation of isomeric glycans. Here, we present a systematic investigation of many different glycan-metal ion complexes in an attempt to optimize the IMS separation of different isomeric glycans. By selecting optimum glycan-metal ion complexes, partial IMS separation was realized for all the 21 isomeric glycan pairs used in the experimental study. Baseline IMS separation was achieved for 76% of these isomeric glycan pairs. The best IMS separation of isomeric glycans was achieved in some cases by incorporating multiple ions with a glycan, such as the complex [glycan + Ca + Cl]+. In addition, the well-known IMS-MS measurement trendlines, often used to identify specific compound classes, were preserved for glycans even for all the 270 glycan-metal ion complexes observed in IMS-MS spectra.

Genome-wide identification and characterization of the AMPK genes and their distinct expression patterns in response to air exposure in the Manila clam (Ruditapes philippinarum).

INTRODUCTION: AMP-activated protein kinases (AMPK) are heterotrimeric complexes. The main upstream phosphorylase has AMP-dependent LKB1 and Ca2+-dependent CaMKK beta. AMPK also includes an auto-inhibitory domain and a region associated with beta and gamma subunits, which regulate a variety of cellular activities and energy metabolism. The increase in the ratio of AMP/ATP can stimulate the activation of AMPK. Once AMPK is activated, pathways to ATP consumption (e.g., fat, cholesterol, and protein synthesis) will be shut down. The pathway to ATP generation (e.g., oxidation of fat and glycolysis pathway) will be activated. AMPK genes have not been systematically characterized in marine invertebrates. METHODS: In this study, we identified and characterized three AMPK genes, AMPK-α, AMPK-ß, and AMPK-γ, in the Manila clam (Ruditapes philippinarum). To gain insight into the role of AMPK genes during clam energy metabolism, quantitative real-time PCR was used to investigate the expression profiles in the different stages of clam development, in healthy adult tissues, and after air exposure at two different temperatures. RESULTS: Phylogenetic and protein structural analyses were conducted to determine the identity and evolutionary relationships of these genes. The structural features of the genes were relatively well-conserved, relative to the AMPK genes of other vertebrates. The expression of genes was significantly induced 3-48 h after air exposure. CONCLUSINON: AMPK-α, AMPK-ß and AMPK-γ are involved in clam energy metabolism. Increased expression levels of AMPK genes in the gill and intestine of Manila clam in response to air exposure implied a strong adaptability to the coastal environment.

A Grouping Particle Swarm Optimizer with Personal-Best-Position Guidance for Large Scale Optimization.

Particle Swarm Optimization (PSO) is a popular algorithm which is widely investigated and well implemented in many areas. However, the canonical PSO does not perform well in population diversity maintenance so that usually leads to a premature convergence or local optima. To address this issue, we propose a variant of PSO named Grouping PSO with Personal-Best-Position ( Pbest) Guidance (GPSO-PG) which maintains the population diversity by preserving the diversity of exemplars. On one hand, we adopt uniform random allocation strategy to assign particles into different groups and in each group the losers will learn from the winner. On the other hand, we employ personal historical best position of each particle in social learning rather than the current global best particle. In this way, the exemplars diversity increases and the effect from the global best particle is eliminated. We test the proposed algorithm to the benchmarks in CEC 2008 and CEC 2010, which concern the large scale optimization problems (LSOPs). By comparing several current peer algorithms, GPSO-PG exhibits a competitive performance to maintain population diversity and obtains a satisfactory performance to the problems.

A Distance-Based Weighted Undersampling Scheme for Support Vector Machines and its Application to Imbalanced Classification.

A support vector machine (SVM) plays a prominent role in classic machine learning, especially classification and regression. Through its structural risk minimization, it has enjoyed a good reputation in effectively reducing overfitting, avoiding dimensional disaster, and not falling into local minima. Nevertheless, existing SVMs do not perform well when facing class imbalance and large-scale samples. Undersampling is a plausible alternative to solve imbalanced problems in some way, but suffers from soaring computational complexity and reduced accuracy because of its enormous iterations and random sampling process. To improve their classification performance in dealing with data imbalance problems, this work proposes a weighted undersampling (WU) scheme for SVM based on space geometry distance, and thus produces an improved algorithm named WU-SVM. In WU-SVM, majority samples are grouped into some subregions (SRs) and assigned different weights according to their Euclidean distance to the hyper plane. The samples in an SR with higher weight have more chance to be sampled and put to use in each learning iteration, so as to retain the data distribution information of original data sets as much as possible. Comprehensive experiments are performed to test WU-SVM via 21 binary-class and six multiclass publically available data sets. The results show that it well outperforms the state-of-the-art methods in terms of three popular metrics for imbalanced classification, i.e., area under the curve, F-Measure, and G-Mean.

Novel one- and two-dimensional Zn(II) coordination polymers based on a versatile 3,6-bis(pyridin-4-yl)phenanthrene-9,10-dione ligand.

Two new Zn(II) coordination polymers, namely, catena-poly[[dibromidozinc(II)]-µ-[3,6-bis(pyridin-4-yl)phenanthrene-9,10-dione-κ(2)N:N']], [ZnBr2(C24H14N2O2)]n, (1), and poly[[bromido[µ3-10-hydroxy-3,6-bis(pyridin-4-yl)phenanthren-9-olato-κ(3)N:N':O(9)]zinc(II)] hemihydrate], {[ZnBr(C24H15N2O2)]·0.5H2O}n, (2), have been synthesized through hydrothermal reaction of ZnBr2 and a 60° angular phenanthrenedione-based linker, i.e. 3,6-bis(pyridin-4-yl)phenanthrene-9,10-dione, in different solvent systems. Single-crystal analysis reveals that polymer (1) features one-dimensional zigzag chains connected by weak C-H...π and π-π interactions to form a two-dimensional network. The two-dimensional networks are further stacked in an ABAB fashion along the a axis through C-H...O hydrogen bonds. Layers A and B comprise left- and right-handed helical chains, respectively. Coordination polymer (2) displays a wave-like two-dimensional layered structure with helical chains. In this compound, there are two opposite helical -Zn-HL- chains [HL is 10-hydroxy-3,6-bis(pyridin-4-yl)phenanthren-9-olate] in adjacent layers. The layers are packed in an ABAB sequence and are further connected through O-H...Br and O-H...O hydrogen-bond interactions to form a three-dimensional framework. In (1) and (2), the mutidentate L and HL ligands exhibits different coordination modes.

Observability of Boolean control networks with state time delays.

This brief deals with the problem of the observability for the Boolean control networks with time delays in states. First, using semi-tensor product of matrices and the matrix expression of logic, the Boolean control networks with state delays can be converted into discrete time delay dynamics. Then, the observability of the Boolean control networks via two kinds of inputs is investigated by giving necessary and sufficient conditions. Finally, examples are given to illustrate the efficiency of the obtained results.