International remittance flows and the economic and social consequences of COVID-19

One of the possible consequences of the tightening of international borders during and after pandemic COVID-19 is what the World Economic Forum refers to as the ‘throttling’ of international (labour) migration. While this will have a profound macroeconomic impact on the global economy, the potential impact on remittances on families, communities and national economies could be equally marked. We present a chord diagram to visualize the latest inter- (and intra-) regional global data on international remittances. This graphic shows the degree of the interconnectedness of the ‘global economy of work’ and the extent to which negative health, economic, social or political changes for migrants in one territory will have profound consequences far across the world

Circular visualization of China’s internal migration flows 2010–2015

We adapted the chord diagram plot to visualize China’s recent inter-provincial migration during 2010–2015. The arrowheads were added to present the direction of the flows. This method allows us to show the complete migration flows between 31 provinces in China including the direction and volume of the flows. The spatial component was also clearly depicted in the plot using four color palates representing four regions in China (i.e. East, Center, West, Northeast) and arranging the 31 provinces in an approximate geographic order. Besides that, we extend the chord diagram plot to describe China’s bilateral net migration during 2010–2015

Changing internal migration flows patterns in South Korea

In comparison with other developed nations, there is a relative lack of analyses on internal migration flow in South Korea. During the last 50 years, the country has witnessed distinct changes in both the levels and patterns of internal migration. Traditionally, the faster developing north-west administrative units (Seoul, Incheon and Gyeonggi regions) have accounted for the majority of in-migration. However, since 2011, internal migration in Korea has become more diffuse, with migrants moving to a greater variety of regions. We visualize these changes using chord diagram plots

AMADA-Analysis of Multidimensional Astronomical Datasets

We present AMADA, an interactive web application to analyse multidimensional datasets. The user uploads a simple ASCII file and AMADA performs a number of exploratory analysis together with contemporary visualizations diagnostics. The package performs a hierarchical clustering in the parameter space, and the user can choose among linear, monotonic or non-linear correlation analysis. AMADA provides a number of clustering visualization diagnostics such as heatmaps, dendrograms, chord diagrams, and graphs. In addition, AMADA has the option to run a standard or robust principal components analysis, displaying the results as polar bar plots. The code is written in R and the web interface was created using the Shiny framework. AMADA source-code is freely available at https://goo.gl/KeSPue, and the shiny-app at http://goo.gl/UTnU7I.Comment: Accepted for publication in Astronomy & Computin

Internal migration in Brazil using circular visualization

In Brazil – a developing country and one that in its last census in 2010 presented a number of five-year interstate migrations of approximately 4.6 million people – the study of internal migration is a complex exercise given the size and diversity of the country. We adapted the chord diagram plot to visualize the bilateral interstate migration flows in Brazil over a five-year period of 2005–10, and the migration stocks in Brazil in 2010. The bilateral migration flows highlight some recent trends of interstate migration (observed in recent decades), in turn different from cumulative flows over a long period (migration stocks). Brazilian internal migration in the new millennium seems to be marked by the inability of destination areas to absorb migrants over long periods, by the return migration to areas of origin and by the emergence of new areas of retention of migrants

Spatial Pathomics Toolkit for Quantitative Analysis of Podocyte Nuclei with Histology and Spatial Transcriptomics Data in Renal Pathology

Podocytes, specialized epithelial cells that envelop the glomerular capillaries, play a pivotal role in maintaining renal health. The current description and quantification of features on pathology slides are limited, prompting the need for innovative solutions to comprehensively assess diverse phenotypic attributes within Whole Slide Images (WSIs). In particular, understanding the morphological characteristics of podocytes, terminally differentiated glomerular epithelial cells, is crucial for studying glomerular injury. This paper introduces the Spatial Pathomics Toolkit (SPT) and applies it to podocyte pathomics. The SPT consists of three main components: (1) instance object segmentation, enabling precise identification of podocyte nuclei; (2) pathomics feature generation, extracting a comprehensive array of quantitative features from the identified nuclei; and (3) robust statistical analyses, facilitating a comprehensive exploration of spatial relationships between morphological and spatial transcriptomics features.The SPT successfully extracted and analyzed morphological and textural features from podocyte nuclei, revealing a multitude of podocyte morphomic features through statistical analysis. Additionally, we demonstrated the SPT's ability to unravel spatial information inherent to podocyte distribution, shedding light on spatial patterns associated with glomerular injury. By disseminating the SPT, our goal is to provide the research community with a powerful and user-friendly resource that advances cellular spatial pathomics in renal pathology. The implementation and its complete source code of the toolkit are made openly accessible at https://github.com/hrlblab/spatial_pathomics

Dual-RNAseq Analysis Unravels Virus-Host Interactions of MetSV and Methanosarcina mazei

Methanosarcina spherical virus (MetSV), infecting Methanosarcina species, encodes 22 genes, but their role in the infection process in combination with host genes has remained unknown. To study the infection process in detail, infected and uninfected M. mazei cultures were compared using dual-RNAseq, qRT-PCRs, and transmission electron microscopy (TEM). The transcriptome analysis strongly indicates a combined role of virus and host genes in replication, virus assembly, and lysis. Thereby, 285 host and virus genes were significantly regulated. Within these 285 regulated genes, a network of the viral polymerase, MetSVORF6, MetSVORF5, MetSVORF2, and the host genes encoding NrdD, NrdG, a CDC48 family protein, and a SSB protein with a role in viral replication was postulated. Ultrastructural analysis at 180 min p.i. revealed many infected cells with virus particles randomly scattered throughout the cytoplasm or attached at the cell surface, and membrane fragments indicating cell lysis. Dual-RNAseq and qRT-PCR analyses suggested a multifactorial lysis reaction in potential connection to the regulation of a cysteine proteinase, a pirin-like protein and a HicB-solo protein. Our study's results led to the first preliminary infection model of MetSV infecting M. mazei, summarizing the key infection steps as follows: replication, assembly, and host cell lysis

Regulatory network analysis in estradiol-treated human endothelial cells.

Background/Aims: Estrogen has been reported to have beneficial effects on vascular biology through direct actions on endothelium. Together with transcription factors, miRNAs are the major drivers of gene expression and signaling networks. The objective of this study was to identify a com-prehensive regulatory network (miRNA-transcription factor-downstream genes) that controls the transcriptomic changes observed in endothelial cells exposed to estradiol. Methods: miR-NA/mRNA interactions were assembled using our previous microarray data of human umbilical vein endothelial cells (HUVEC) treated with 17ß- Estradiol (E2) (1 nmol/lL, 24 h). miRNA--mRNA pairings and their associated canonical pathways were determined using Ingenuity Pathway Analysis software. Transcription factors were identified among the miR-NA-regulated genes. Transcription factor downstream target genes were predicted by consensus transcription factor binding sites in the promoter region of E2-regulated genes by using JASPAR and TRANSFAC tools in Enrichr software. Results: miRNA--target pairings were filtered by using differentially expressed miRNAs and mRNAs characterized by a regulatory relationship accord-ing to miRNA target prediction databases. The analysis identified 588 miRNA--target interactions between 102 miRNAs and 588 targets. Specifically, 63 up-regregulated miRNAs interacted with 295 down-regregulated targets, while 39 down-regregulated miRNAs were paired with 293 up-regregulated mRNA targets. Functional characterization of miRNA/mRNA association analy-sis highlighted hypoxia signallignaling, integrin, ephrin receptor signaling, and regulation of actin-based motility by Rho among the canonical pathways regulated by E2 in HUVEC. Tran-scription factors and downstream genes analysis revealed a total of eight networks, including those mediated by JUN and REPIN1, which are associated with cadherin binding and cell adhe-sion molecule binding pathways. Conclusion: This study identifies regulatory networks obtained by integrative microarray analysis and provides additional insights into the way estradiol could regulate endothelial function in human endothelial cells

Information to the eye of the beholder: data visualization for many-objective optimization

The visualization gap is one of the important challenges posed by many-objective optimization problems (MaOPs). In this paper, we present an integrated data visualization method for MaOPs, called CAP-vis plot, combining the Chord diagram, the Angular mapping and the Parallel coordinates in the same visualization. The method follows the circular design layout, showing different levels of information. This new approach allows the spatial location of points in high dimensional spaces, the visualization of harmony and conflict between objectives, as well as the comparison of the approximation sets provided by different algorithms. With this work, we try to fill the visualization gap and bring information to the eye of the decision-maker and the optimizer, with an intuitive overview of the obtained results. Some experiments were performed using the Benchmark Functions proposed for the IEEE-CEC 2018 Competition on Many-Objective Optimization. We used the tool to visualize the results obtained by NSGA-III, HypE, RVEA, MOEA/DD, PICEA-g, using the PlatEMO MATLAB platform, with the same parameter settings of the competition. The results on the Benchmark Problems show the importance of the qualitative analysis of the data. The experiments show how visualization can help interpretation of the results and identification of strengths and drawbacks of MOEA.The authors would like to thank the Brazilian agencies CAPES, CNPq and FAPEMIG for the financial support

Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.

Abstract: Although several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strate-gies for the Portuguese Holstein cattle population considering several commercially available single nucleotide poly-morphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with theirgenotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate rang-ing from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation