The First Illumina-Based De Novo Transcriptome Sequencing and Analysis of Safflower Flowers

BACKGROUND: The safflower, Carthamus tinctorius L., is a worldwide oil crop, and its flowers, which have a high flavonoid content, are an important medicinal resource against cardiovascular disease in traditional medicine. Because the safflower has a large and complex genome, the development of its genomic resources has been delayed. Second-generation Illumina sequencing is now an efficient route for generating an enormous volume of sequences that can represent a large number of genes and their expression levels. METHODOLOGY/PRINCIPAL FINDINGS: To investigate the genes and pathways that might control flavonoids and other secondary metabolites in the safflower, we used Illumina sequencing to perform a de novo assembly of the safflower tubular flower tissue transcriptome. We obtained a total of 4.69 Gb in clean nucleotides comprising 52,119,104 clean sequencing reads, 195,320 contigs, and 120,778 unigenes. Based on similarity searches with known proteins, we annotated 70,342 of the unigenes (about 58% of the identified unigenes) with cut-off E-values of 10(-5). In total, 21,943 of the safflower unigenes were found to have COG classifications, and BLAST2GO assigned 26,332 of the unigenes to 1,754 GO term annotations. In addition, we assigned 30,203 of the unigenes to 121 KEGG pathways. When we focused on genes identified as contributing to flavonoid biosynthesis and the biosynthesis of unsaturated fatty acids, which are important pathways that control flower and seed quality, respectively, we found that these genes were fairly well conserved in the safflower genome compared to those of other plants. CONCLUSIONS/SIGNIFICANCE: Our study provides abundant genomic data for Carthamus tinctorius L. and offers comprehensive sequence resources for studying the safflower. We believe that these transcriptome datasets will serve as an important public information platform to accelerate studies of the safflower genome, and may help us define the mechanisms of flower tissue-specific and secondary metabolism in this non-model plant

Two Novel HSD17B4 Heterozygous Mutations in Association With D-Bifunctional Protein Deficiency: A Case Report and Literature Review

Aims!#!Combination of anti-angiogenesis therapy and immunotherapy has showed synergistic effects in non-small cell lung cancer (NSCLC). The aim of this retrospective study was to investigate the efficacy and safety of anlotinib with and without immunotherapy in NSCLC.!##!Methods!#!Pathologically confirmed NSCLC patients (stage IIIB-IV) receiving anlotinib between November 2018 and February 2020 were enrolled for retrospective analysis. The outcomes and safety of overall patients were evaluated, and the efficacies of anlotinib plus immunotherapy and anlotinib alone was compared. The primary endpoint was progression-free survival (PFS).!##!Results!#!A total of 80 patients (median age: 62 years, range: 29-86 years) were included. Overall median PFS was 4.3 months (95% confidence interval (CI): 2.7-5.9 months). In univariate analysis, patients without !##!Conclusion!#!Anlotinib is well tolerable and effective in advanced NSCLC patients. Brain metastasis is an independent predictor of PFS in NSCLC patients receiving anlotinib. Future prospective studies with larger sample size and extended follow-up are needed to confirm the clinical benefit in NSCLC patients treated with anlotinib combined with immunotherapy

Multi-Scale Massive Points Fast Clustering Based on Hierarchical Density Spanning Tree

Spatial clustering is dependent on spatial scales. With the widespread use of web maps, a fast clustering method for multi-scale spatial elements has become a new requirement. Therefore, to cluster and display elements rapidly at different spatial scales, we propose a method called Multi-Scale Massive Points Fast Clustering based on Hierarchical Density Spanning Tree. This study refers to the basic principle of Clustering by Fast Search and Find of Density Peaks aggregation algorithm and introduces the concept of a hierarchical density-based spanning tree, combining the spatial scale with the tree links of elements to propose the corresponding pruning strategy, and finally realizes the fast multi-scale clustering of elements. The first experiment proved the time efficiency of the method in obtaining clustering results by the distance-scale adjustment of parameters. Accurate clustering results were also achieved. The second experiment demonstrated the feasibility of the method at the aggregation point element and showed its visual effect. This provides a further explanation for the application of tree-link structures

Spatial Downscaling of NPP-VIIRS Nighttime Light Data Using Multiscale Geographically Weighted Regression and Multi-Source Variables

Remote sensing images of nighttime lights (NTL) were successfully used at global and regional scales for various applications, including studies on population, politics, economics, and environmental protection. The Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data has the advantages of high temporal resolution, long coverage time series, and wide spatial range. The spatial resolution of the monthly and annual composite data of NPP-VIIRS NTL is only 500 m, which hinders studies requiring higher resolution. We propose a multi-source spatial variable and Multiscale Geographically Weighted Regression (MGWR)-based method to achieve the downscaling of NPP-VIIRS NTL data. An MGWR downscaling framework was implemented to obtain NTL data at 120 m resolution based on auxiliary data representing socioeconomic or physical geographic attributes. The downscaled NTL data were validated against LuoJia1-01 imagery based on the coefficient of determination (R2) and the root-mean-square error (RMSE). The results suggested that the spatial resolution of the data was enhanced after downscaling, and the MGWR-based downscaling results demonstrated higher R2 (R2 = 0.9141) and lower RMSE than those of Geographically Weighted Regression and Random Forest-based algorithms. Additionally, MGWR can reveal the different relationships between multiple auxiliary and NTL data. Therefore, this study demonstrates that the spatial resolution of NPP-VIIRS NTL data is improved from 500 m to 120 m upon downscaling, thereby facilitating NTL-based applications

Quantification of EUGR as a Measure of the Quality of Nutritional Care of Premature Infants.

To develop an index of the quality of nutritional care of premature infants based on the change in weight Z score from birth to discharge and to illustrate the use of this index in comparing the performance of different NICUs.Retrospective data analysis was performed to compare the growth of premature infants born in three perinatal centers. Infants with gestational age ≤ 32 weeks who survived to discharge from 2006 to 2010 were included. Weight Z scores at birth and discharge were calculated by the method of Fenton. Using data from one NICU as the reference, a multivariable linear regression model of change in weight Z score from birth to discharge was developed. Employing this model, a benchmark value of change in weight Z score was calculated for each baby. The difference between this calculated benchmark value and the baby's observed change in weight Z score was defined as the performance gap for that infant. The average value of the performance gaps in a NICU serves as its quality care index.1,714 infants were included for analysis. Change in weight Z score is influenced by birth weight Z score and completed weeks of gestation; thus the model for calculating the benchmark change in weight Z score was adjusted for these two variables. We found statistically significant differences in the average performance gaps for the three units.A quality care index was developed based on change in weight Z score from birth to discharge adjusted for two initial risk factors. This objective, easily calculated index may be used as a measurement of the quality of nutritional care to rank the performance of different NICUs

Spatial Downscaling of NPP-VIIRS Nighttime Light Data Using Multiscale Geographically Weighted Regression and Multi-Source Variables

Remote sensing images of nighttime lights (NTL) were successfully used at global and regional scales for various applications, including studies on population, politics, economics, and environmental protection. The Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data has the advantages of high temporal resolution, long coverage time series, and wide spatial range. The spatial resolution of the monthly and annual composite data of NPP-VIIRS NTL is only 500 m, which hinders studies requiring higher resolution. We propose a multi-source spatial variable and Multiscale Geographically Weighted Regression (MGWR)-based method to achieve the downscaling of NPP-VIIRS NTL data. An MGWR downscaling framework was implemented to obtain NTL data at 120 m resolution based on auxiliary data representing socioeconomic or physical geographic attributes. The downscaled NTL data were validated against LuoJia1-01 imagery based on the coefficient of determination (R2) and the root-mean-square error (RMSE). The results suggested that the spatial resolution of the data was enhanced after downscaling, and the MGWR-based downscaling results demonstrated higher R2 (R2 = 0.9141) and lower RMSE than those of Geographically Weighted Regression and Random Forest-based algorithms. Additionally, MGWR can reveal the different relationships between multiple auxiliary and NTL data. Therefore, this study demonstrates that the spatial resolution of NPP-VIIRS NTL data is improved from 500 m to 120 m upon downscaling, thereby facilitating NTL-based applications

Gut microbiota is involved in the alleviation of loperamide-induced constipation by honey supplementation in mice

Constipation is one of the most common functional gastrointestinal disorders accompanied with intestinal dysbiosis. Laxatives for constipation usually have side effects. Bee honey is a natural food with unique composition, antimicrobial properties, and bifidogenic effect. In order to assess whether honey can ameliorate loperamide-induced constipation in BALB/c mice through the alteration of the gut microbiota, the present study was undertaken. Mice were given Jarrah honey (7.5 g/kg body weight) by gavage once per day for 5 days. Fecal water content, intestinal transit rate together with the colon concentrations of substance P (SP), vasoactive intestinal peptide (VIP), and serotonin (5-hydroxytryptamine; 5-HT) were evaluated. Furthermore, we determined the effect of honey treatment on gut microbiota in mice using stool genomic 16S rRNA sequencing. As a result, honey showed an obvious improvement in fecal water content and alleviated constipation by modulating the microbial composition of the microbiota, and this was highly associated with a proportional decrease in gut Desulfovibrio. In addition, we found that the colon level of neurotransmitters SP and VIP was significantly related to microbial variations. Our results indicate that gut microbiota is involved in the alleviation of loperamide-induced constipation by honey supplementation in mice, and it could be considered as an evaluating parameter in constipation therapy strategies

PELP1 Suppression Inhibits Gastric Cancer Through Downregulation of c-Src-PI3K-ERK Pathway

Background: Proline-, glutamic acid-, and leucine-rich protein 1 (PELP1), a co-activator of estrogen receptors alpha, was confirmed to be directly associated with the oncogenic process of multiple cancers, especially hormone-dependent cancers. The purpose of our research was to explore the biological function, clinical significance, and therapeutic targeted value of PELP1 in gastric cancer (GC). Methods: The expression status of PELP1 in GC cell lines or tissues was analyzed through bioinformatics data mining. Thirty-six GC tissue chip was applied to demonstrate the results of bioinformatics data mining assayed by immunohistochemical method. The expression status of PELP1 in GC cell lines was also analyzed using western blot. Correlation analysis between PELP1 expression and clinicopathological parameter was performed. Kaplan-Meier survival analysis was applied to analyze the relationship between PELP1 expression and total survival time. Three pairs of siRNA were designed to silence the expression of PELP1 in GC. After PELP1 was silenced by siRNA or activated by saRNA, the growth, plate colony formation, migration and invasion ability of the GC cell or normal gastric epithelium cell line was tested in vitro. Cell cycle was tested by flow cytometry. Nude mice xenograft experiment was performed after PELP1 was silenced. The downstream molecular pathway regulated by PELP1 was explored. Molecular docking tool was applied to combine chlorpromazine with PELP1. The inhibitory effect of chlorpromazine in GC was assayed, then it was tested whether PELP1 was a therapeutic target of chlorpromazine in GC. Results: PELP1 expression was elevated in GC cell lines and clinical GC tissue samples. PELP1 silence by siRNA compromised the malignant traits of GC. PELP1 expression positively correlated with tumor invasion depth, lymph node metastasis, tissue grade, TNM stage, but had no correlation with patient age, sex, tumor size, and tumor numbers. Kaplan-Meier survival analysis revealed high PELP1 expression had a shorter survival period in GC patients after follow-up. Q-PCR and western blot revealed PELP1 suppression in GC decreased expression of the c-Src-PI3K-ERK pathway. It was also implied that chlorpromazine (CPZ) can inhibit the malignant traits of GC and downregulate the expression of PELP1. Conclusions: In a word, PELP1 is an oncogene in gastric cancer and c-Src-PI3K-ERK pathway activation may be responsible for its tumorigenesis, PELP1 may be a potential therapeutic target of chlorpromazine in GC.</p

Gut microbiota is involved in the alleviation of loperamide‐induced constipation by honey supplementation in mice

Constipation is one of the most common functional gastrointestinal disorders accompanied with intestinal dysbiosis. Laxatives for constipation usually have side effects. Bee honey is a natural food with unique composition, antimicrobial properties, and bifidogenic effect. In order to assess whether honey can ameliorate loperamide-induced constipation in BALB/c mice through the alteration of the gut microbiota, the present study was undertaken. Mice were given Jarrah honey (7.5 g/kg body weight) by gavage once per day for 5 days. Fecal water content, intestinal transit rate together with the colon concentrations of substance P (SP), vasoactive intestinal peptide (VIP), and serotonin (5-hydroxytryptamine; 5-HT) were evaluated. Furthermore, we determined the effect of honey treatment on gut microbiota in mice using stool genomic 16S rRNA sequencing. As a result, honey showed an obvious improvement in fecal water content and alleviated constipation by modulating the microbial composition of the microbiota, and this was highly associated with a proportional decrease in gut Desulfovibrio. In addition, we found that the colon level of neurotransmitters SP and VIP was significantly related to microbial variations. Our results indicate that gut microbiota is involved in the alleviation of loperamide-induced constipation by honey supplementation in mice, and it could be considered as an evaluating parameter in constipation therapy strategies

Annotation of cell types (ACT): a convenient web server for cell type annotation

Abstract Background The advancement of single-cell sequencing has progressed our ability to solve biological questions. Cell type annotation is of vital importance to this process, allowing for the analysis and interpretation of enormous single-cell datasets. At present, however, manual cell annotation which is the predominant approach remains limited by both speed and the requirement of expert knowledge. Methods To address these challenges, we constructed a hierarchically organized marker map through manually curating over 26,000 cell marker entries from about 7000 publications. We then developed WISE, a weighted and integrated gene set enrichment method, to integrate the prevalence of canonical markers and ordered differentially expressed genes of specific cell types in the marker map. Benchmarking analysis suggested that our method outperformed state-of-the-art methods. Results By integrating the marker map and WISE, we developed a user-friendly and convenient web server, ACT ( http://xteam.xbio.top/ACT/ or http://biocc.hrbmu.edu.cn/ACT/ ), which only takes a simple list of upregulated genes as input and provides interactive hierarchy maps, together with well-designed charts and statistical information, to accelerate the assignment of cell identities and made the results comparable to expert manual annotation. Besides, a pan-tissue marker map was constructed to assist in cell assignments in less-studied tissues. Applying ACT to three case studies showed that all cell clusters were quickly and accurately annotated, and multi-level and more refined cell types were identified. Conclusions We developed a knowledge-based resource and a corresponding method, together with an intuitive graphical web interface, for cell type annotation. We believe that ACT, emerging as a powerful tool for cell type annotation, would be widely used in single-cell research and considerably accelerate the process of cell type identification