As one of the oldest agricultural crops in China, millet (Panicum miliaceum) has powerful drought tolerance. In this study, transcriptome and metabolome analyses of ‘Hequ Red millet’ (HQ) and ‘Yanshu No.10’ (YS10) millet after 6 h of drought stress were performed. Transcriptome characteristics of drought stress in HQ and YS10 were characterized by Pacbio full-length transcriptome sequencing. The pathway analysis of the differentially expressed genes (DEGs) showed that the highly enriched categories were related to starch and sucrose metabolism, pyruvate metabolism, metabolic pathways, and the biosynthesis of secondary metabolites when the two millet varieties were subjected to drought stress. Under drought stress, 245 genes related to energy metabolism were found to show significant changes between the two strains. Further analysis showed that 219 genes related to plant hormone signal transduction also participated in the drought response. In addition, numerous genes involved in anthocyanin metabolism and photosynthesis were confirmed to be related to drought stress, and these genes showed significant differential expression and played an important role in anthocyanin metabolism and photosynthesis. Moreover, we identified 496 transcription factors related to drought stress, which came from 10 different transcription factor families, such as bHLH, C3H, MYB, and WRKY. Further analysis showed that many key genes related to energy metabolism, such as citrate synthase, isocitrate dehydrogenase, and ATP synthase, showed significant upregulation, and most of the structural genes involved in anthocyanin biosynthesis also showed significant upregulation in both strains. Most genes related to plant hormone signal transduction showed upregulated expression, while many JA and SA signaling pathway-related genes were downregulated. Metabolome analysis was performed on ‘Hequ red millet’ (HQ) and ‘Yanshu 10’ (YS10), a total of 2082 differential metabolites (DEMs) were identified. These findings indicate that energy metabolism, anthocyanins, photosynthesis, and plant hormones are closely related to the drought resistance of millet and adapt to adversity by precisely regulating the levels of various molecular pathways.

Highlights d Using two cutoffs to segment omics data outperforms single cutoffs in hit selection d Pathway enrichment and network analysis provide contrasting solutions and trade-offs d Iterative selection by pathway, then network analysis, shows improved performance d Hit selection by this iterative method can be done rapidly using the SIGNAL website

PurposeTo assess the prevalence of refractive errors (REs) in school children aged 6–18 years in urban and rural settings in Dalian, Northeast of China.MethodsThis is a school-based cross-sectional survey using multi-stage randomization technique. Six- to eighteen-year-old school children from elementary schools, junior and senior high schools from a rural area and an urban area in Dalian were included in December 2018. All subjects underwent a comprehensive questionnaire and eye examination.ResultsA total of 4,522 school children with 6–18 years of age were investigated. The age, gender-adjusted prevalence of myopia, and anisometropia were 82.71 and 7.27% among the urban students as compared to 71.76% and 5.41% among the rural ones (OR = 1.80, 95 % CI = 1.53 - 2.11, P < 0.001; OR = 1.29, 95 % CI = 1.00–1.67, P = 0.049), respectively. The hyperopia was less common in urban students than in rural ones (5.63 vs. 10.21%; OR = 0.54, 95 % CI: 0.43–0.67, P < 0.001). However, there was no significant difference in prevalence of astigmatism between urban (46.07%) and rural (44.69%) participants (OR = 0.96, 95 % CI: 0.84–1.10, P = 0.559). The differences on prevalence of REs were attributed to different social-demographic and physiologic factors.ConclusionsThe students from urban settings are more likely to have myopia and anisometropia but less likely to have hyperopia than their rural counterparts. Although considerable attention had been paid to controlling REs, it is necessary to further consider the urban-rural differences in REs.

Comprehensive and efficient gene hit selection from high throughput assays remains a critical bottleneck in realizing the potential of genome-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs, and are often combined in an ad hoc manner. The specific limitations of these individual approaches, the lack of a systematic way by which to integrate their rankings, and the inaccessibility of complex computational approaches to many researchers, has contributed to unexpected variability and limited overlap in the reported results from comparable genome-wide studies. Using a set of three highly studied genome-wide datasets for HIV host factors that have been broadly cited for their limited number of shared candidates, we characterize the specific complementary contributions of commonly used analysis approaches and find an optimal framework by which to integrate these methods. We describe Throughput Ranking by Iterative Analysis of Genomic Enrichment (TRIAGE), an integrated, iterative approach which uses pathway and network statistical methods and publicly available databases to optimize gene prioritization. TRIAGE is accessible as a secure, rapid, user-friendly web-based application (https://triage.niaid.nih.gov).

Objective. To study the development process of the human retina, we analyzed the development track of main cell types and transitional cell populations, identifying the retinal organoid cell differentiation-related genes (RDRGs). Methods. Single-cell RNA sequencing data (scRNA-Seq) of human retinal organoids were downloaded from Gene Expression Omnibus (GEO) database in this study. Data were processed with quality analysis and analysis of variance. Principal component analysis and t -distributed stochastic neighbor embedding were used to conduct dimension reduction analysis and type annotation for the screened data. Marker genes and RDRGs were identified by differential analysis. Cell differentiation characteristics were determined by trajectory analysis. Enrichment pathways were analyzed by Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG), and functional modules were obtained by protein-protein interaction (PPI) network analysis. Results. iPSCs were mainly located at the root of differentiation trajectory, while neurons and astrocytes were distributed in different branches, respectively. Meanwhile, 220 RDRGs were obtained. They were involved in the biological functions related to vision and visual development, as well as significantly enriched in signaling pathways associated with retinal vascular development and retinal neuroregulation. Protein-protein interaction network construction and functional subnetwork analysis were conducted on RDRGs, and two functional submodules were obtained. The enrichment analysis presented that the two submodules played a vital role in retinal development, visual perception, and cell respiration. Conclusions. This study identified RDRGs and revealed the biological functions involved in these genes, which are expected to provide evidence for researching retinal development and diseases.

The paper proposed the management and monitoring system of automatic tridimensional warehouse based on network communication, the main characters and realization of communication program developing with VC6 are expounded in the paper based on industrial Ethernet communication. the system is divided into the automated warehouse management and control system functional modules. And the communication model between the supervisor computer and the ARM2440 is presented. Experimental results show that the design has lower cost and achieves system integration management and control function.

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Discretization plays an important role in data pre-processing and has been used in fields such as artificial intelligence and data mining. A new discretization algorithm based on binary ant colony and variable precision rough set is proposed in this paper. Binary ant network is first built using candidate breakpoints, then global optimal breakpoints is searched in the network. The fitness function is established by the number of breakpoints and approximation classification accuracy of variable precision rough set. This method is compared with other algorithms using C4.5 classifier on the WEKA (Waikato Environment for Knowledge Analysis) platform and seven UCI data sets. The results indicate that the proposed method performs well.