Interactive Map Research Articles

Genome sequence of the sugarcane aphid, Melanaphis sacchari (Hemiptera: Aphididae).

The sugarcane aphid, Melanaphis sacchari (Zehntner, 1897), is an agricultural pest that causes damage to plants in the Poaceae (the grasses) family, such as sorghum and sugarcane. Here, we used Nanopore long reads and Hi-C interaction map to generate a chromosome-level assembly with a total length of 356.1 Mb, of which 85.5% (304.6 Mb) is contained within the three autosomes and the X chromosome. Repetitive sequences accounted for 16.29% of the chromosomes and a total of 12,530 protein-coding genes were annotated, achieving 95.8% benchmarking universal single-copy orthologs (BUSCO) gene completeness. This offers a substantial improvement compared to previous low-quality genomic resources. Phylogenomic analysis by comparing M. sacchari with twenty-four published aphid genomes representing three aphid tribes reveals that M. sacchari belongs to the tribe Aphidini and maintained a conserved chromosome structure with other Aphidini species. The high-quality genomic resources reported in this study will be useful for understanding the evolution of aphid genomes and studying pest management of M. sacchari.

Constricting Gaps: Protocol development, implementation challenges and lessons learned for the reality map of unmet needs for Palliative Care Interventions in advanced cancer patients study in Romania and Switzerland

BackgroundPatients with advanced cancer experience many symptoms and needs requiring a Palliative Care Intervention (PCI). Identifying gaps between needs for PCIs and experienced delivery may improve health care, furthermore the association of gaps with quality indicators (QI). The multicentre Romanian (RO)-Swiss (CH) reality map study implemented a novel protocol based on needs concepts and culturally adapted quality indicators (QI). MethodsAn interactive mapping guide measuring unmet needs for PCIs monthly over six months, patient characteristics (cognition, EAPC basic data set, Cofactors) and QI (Inappropriate Anticancer Treatment, High Symptom Burden [IPOS, EQ5D], Repeated ER Admissions, Aggressive End-of-Life Care, and Quality of Death-and-Dying) were developed, applying swiss standards for quality assurance. A composite endpoint (QI, cofactors) was planned. Finally, local solutions responding to gaps were piloted. ResultsFrom 308 patients (RO: 262, CH: 46, age 62j [mean], 74 % ECOG PS 1&2, 81 % current anticancer treatment) baseline and first follow-up data revealed main gaps (symptom management, spiritual needs, family support), country differences (e.g. illness understanding, spiritual needs) and a significant association of the number of gaps with depression. Later data become less, and data quality on QI variable, revealing gaps in research conduct competences, resources, and applicability of over-sophisticated quality assurance tools. Nevertheless, the unmet needs data promoted local initiatives, 81 patients participated in feasibility studies. Finally, the joint experience stimulated academic developments and national integration of palliative care into oncology. ConclusionsPairing motivation and enthusiasm with more modest aims, feasibility testing of all outcomes and investment in research competences may disperse gaps.

3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: An open-source catalog of findings.

The relatively few conditions and family member types (e.g., sibling, parent) considered in investigations of family health history in autism spectrum disorder (ASD, or autism) limits understanding of the role of family history in autism etiology. For more comprehensive understanding and hypothesis-generation, we produced an open-source catalog of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are cataloged in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/app/profile/diana.schendel/viz/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and nongenetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.

Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance

Recent advances in high-resolution mapping of spatial interactions among regulatory elements support the existence of complex topological assemblies of enhancers and promoters known as enhancer-promoter hubs or cliques. Yet, organization principles of these multi-interacting enhancer-promoter hubs and their potential role in regulating gene expression in cancer remain unclear. Here, we systematically identify enhancer-promoter hubs in breast cancer, lymphoma, and leukemia. We find that highly interacting enhancer-promoter hubs form at key oncogenes and lineage-associated transcription factors potentially promoting oncogenesis of these diverse cancer types. Genomic and optical mapping of interactions among enhancer and promoter elements further show that topological alterations in hubs coincide with transcriptional changes underlying acquired resistance to targeted therapy in T cell leukemia and B cell lymphoma. Together, our findings suggest that enhancer-promoter hubs are dynamic and heterogeneous topological assemblies with the potential to control gene expression circuits promoting oncogenesis and drug resistance.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk.

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Biophysical mapping of TREM2-ligand interactions reveals shared surfaces for engagement of multiple Alzheimer's disease ligands.

TREM2 is a signaling receptor expressed on microglia that has emerged as an important drug target for Alzheimer's disease and other neurodegenerative diseases. While a number of TREM2 ligands have been identified, little is known regarding the structural details of how they engage. To better understand this, we created a protein library of 28 different TREM2 variants that could be used to map interactions with various ligands using biolayer interferometry. The variants are located in previously identified putative binding surfaces on TREM2 called the hydrophobic site, basic site, and site 2. We found that mutations to the hydrophobic site ablated binding to apoE4 and TDP-43. Competition binding experiments indicated that apoE4 and oAβ42 share overlapping binding sites on TREM2. In contrast, binding to C1q was disrupted most strongly by mutations to the basic site, including R46, with some mutations to the hydrophobic site also attenuating binding, thus suggesting a broader mediation of binding across the two sites. Supporting this, competition experiments indicated that C1q binding could be blocked by both apoE and oAβ42. TREM2 binding to IL-34 was mediated by the basic site at a surface centering on R76. Competition binding experiments validated the unique site for IL-34, showing little to no competition with either oAβ42 or apoE4. However, competition experiments between C1q and IL34 suggest that the ligands compete for binding at the basic site. Altogether, our results suggest that TREM2 utilizes the hydrophobic site (consisting of CDR1, CDR2, and CDR3) as a common site to engage multiple ligands, and uses distinct basic sites to engage others. Our findings imply that pharmaceutical strategies targeting these surfaces might be effective to modulate TREM2 functions.

Systematic identification of post-transcriptional regulatory modules

In our cells, a limited number of RNA binding proteins (RBPs) are responsible for all aspects of RNA metabolism across the entire transcriptome. To accomplish this, RBPs form regulatory units that act on specific target regulons. However, the landscape of RBP combinatorial interactions remains poorly explored. Here, we perform a systematic annotation of RBP combinatorial interactions via multimodal data integration. We build a large-scale map of RBP protein neighborhoods by generating in vivo proximity-dependent biotinylation datasets of 50 human RBPs. In parallel, we use CRISPR interference with single-cell readout to capture transcriptomic changes upon RBP knockdowns. By combining these physical and functional interaction readouts, along with the atlas of RBP mRNA targets from eCLIP assays, we generate an integrated map of functional RBP interactions. We then use this map to match RBPs to their context-specific functions and validate the predicted functions biochemically for four RBPs. This study provides a detailed map of RBP interactions and deconvolves them into distinct regulatory modules with annotated functions and target regulons. This multimodal and integrative framework provides a principled approach for studying post-transcriptional regulatory processes and enriches our understanding of their underlying mechanisms.

Review of regional maternity capital programmes in Russia 2011–2023

The paper presents a comparative analysis of regional maternity capital programmes of 85 Russia’s federal constituents. Their differences in terms of the size of benefits and benefit conditionalities are reviewed both spatially and temporally for the period from 2011 to 2023. The authors created a unified database of existing regional maternity capital programmes and made it publicly available on the Internet1. Interactive maps and data sheets of the programmes detailing their features were prepared. An analysis of their differences was made, and a typology was set up of regional maternity capital programmes aimed at incentivising childbirth of various birth orders.

Interactive Customer Journey Maps for Complex Services

Customer journey maps often assume linear and uniform customer experiences, limiting their effectiveness for complex services. In this article, an interactive customer journey mapping approach is proposed and evaluated in the context of a smart energy sharing platform project.

A Semantic Knowledge Graph of European Mountain Value Chains

The United Nations forecast a significant shift in global population distribution by 2050, with rural populations projected to decline. This decline will particularly challenge mountain areas’ cultural heritage, well-being, and economic sustainability. Understanding the economic, environmental, and societal effects of rural population decline is particularly important in Europe, where mountainous regions are vital for supplying goods. The present paper describes a geospatially explicit semantic knowledge graph containing information on 454 European mountain value chains. It is the first large-size, structured collection of information on mountain value chains. Our graph, structured through ontology-based semantic modelling, offers representations of the value chains in the form of narratives. The graph was constructed semi-automatically from unstructured data provided by mountain-area expert scholars. It is accessible through a public repository and explorable through interactive Story Maps and a semantic Web service. Through semantic queries, we demonstrate that the graph allows for exploring territorial complexities and discovering new knowledge on mountain areas’ environmental, societal, territory, and economic aspects that could help stem depopulation.

The Effects of Using Digital Technologies on High School Geography Learning

In recent years, the integration of digital technologies into educational practices has become a focal point for enhancing student learning experiences across various subjects, including Geography. Following this trend, the present study investigates the effects of digital technology use on high school Geography education by comparing traditional teaching methods with modern, digitally enhanced approaches. Thus, the main aim of the paper was to evaluate whether digital tools such as interactive maps, 3D simulations, and augmented reality can improve student engagement and academic performance in geography classes. A quasi-experimental research design was employed, involving quantitative analyses of student performance data before and after the intervention. The study sample consisted of 50 high school students divided into two groups: one taught using traditional methods and another exposed to digital learning environments. Curricular Geography tests were administered to the two groups, along with surveys and interviews, to assess differences in academic outcomes and engagement levels between the two groups. The findings indicate that students in the digital learning group outperformed their peers in the traditional setting, achieving higher test scores. This may be attributed to the use of interactive digital tools, which facilitated a deeper understanding of geographical concepts and promoted active participation in the learning process. However, the study also highlights challenges such as unequal access to technology and the necessity for ongoing teacher training to effectively implement digital resources. These conclusions and insights have led to several important implications for education. The positive impact of digital learning tools suggests that educational systems should consider integrating more technology into the curriculum to enhance learning outcomes.

Using a Fitbit-based Walking Game to Improve Physical Activity Among U.S. Veterans.

Physical inactivity, hereafter inactivity, is a serious health problem among U.S. veterans, hereafter veterans. Inactive adults are at risk for adverse cardiac events and premature mortality. Specifically, among veterans, inactivity has been associated with a 23% increase in mortality. In order to increase physical activity among veterans, we developed Veterans Affairs (VA) MapTrek, a mobile-phone-based web app that allows users to take a virtual walk in interesting locations around the world while tracking their progress against that of others like themselves on an interactive map. Steps are counted by a commercially available Fitbit triaxial accelerometer, and users see their progress along a predefined scenic path overlaid on Google Maps. The objective of this study was to determine the effectiveness of VA MapTrek to increase physical activity in a population of veterans at risk for obesity-related morbidity. We recruited overweight and obese veterans obtaining care at the Iowa City Veterans Affairs Health Center. Half of the veterans were assigned to participate in VA MapTrek. Each week, participants were assigned virtual walking races (Monday through Saturday), which followed a predetermined route that is displayed on Google Maps. The participant's position on the map is automatically updated each time their Fitbit syncs to their phone. In addition, challenges were issued periodically. Veterans in the control group were only given a Fitbit. We regressed daily step counts on the days of the week, the days since the start of the intervention period, whether the user was in the VA MapTrek or Control group, and an interaction between the study group and the days since the start of the intervention period. We included subject-specific random intercepts and subject-specific random slopes. This model was estimated using Bayesian Hamiltonian Monte Carlo using Stan's No-U-Turns sampler. We set vague, uniform priors on all the parameters. We enrolled 276 participants, but only 251 (102 in the control group and 149 in the VA MapTrek group) contributed data during the intervention period. Our analysis suggests an 86.8% likelihood that the VA MapTrek intervention led to a minimum increase of 1,000 daily steps over the 8-week period, compared to the control group. Throughout the 8-week intervention, we project that VA MapTrek participants would have taken an extra 96,627 steps, equivalent to 77.8 additional kilometers (km) (48.3 additional miles), assuming an average of 1,242 steps per km (2,000 steps per mile). Our study underscores the potential of VA MapTrek as an intervention for promoting walking among veterans who face elevated risks of obesity and cardiac issues. Rural veterans are a high-risk population, and new interventions like VA MapTrek are needed to improve veterans' health.

Towards clinically relevant dose ratios for Cabamiquine and Pyronaridine combination using P. falciparum field isolate data

The selection and combination of dose regimens for antimalarials involve complex considerations including pharmacokinetic and pharmacodynamic interactions. In this study, we use immediate ex vivo P. falciparum field isolates to evaluate the effect of cabamiquine and pyronaridine as standalone treatments and in combination therapy. We feed the data into a pharmacometrics model to generate an interaction map and simulate meaningful clinical dose ratios. We demonstrate that the pharmacometrics model of parasite growth and killing provides a detailed description of parasite kinetics against cabamiquine-susceptible and resistant parasites. Pyronaridine monotherapy provides suboptimal killing rates at doses as high as 720 mg. In contrast, the combination of a single dose of 330 mg cabamiquine and 360 mg pyronaridine provides over 90% parasite killing in most of the simulated patients. The described methodology that combines a rapid, 3R-compliant in vitro method and modelling to set meaningful doses for new antimalarials could contribute to clinical drug development.

Poetry unveiled: Multimodality and aesthetic responses as a fresh approach to teaching and reading verse

AbstractIn secondary English classrooms, poetry is often a text that is least liked because it is viewed as being “inaccessible,” reserved for the elite, and/or too abstract. Part of the reason for this also lies in the traditional, colonial structures of introducing poetry such as relying on canonical texts and close reading analysis. Yet, outside of the classroom poetry is used in more accessible and engaging manners. With the advancements of technology, there also includes multimodal ways in which to read and write poetry that could be much more interesting for both educators and youth. This paper opens a discussion to consider multimodal and aesthetic responses to including poetry such as using digital apps like PhoneMe, a free accessible platform that allows users to post their written poems, record themselves reciting poems, and pin their poems directly on to an interactive digital map. The uniqueness of PhoneMe—a layered multimodal approach—can provide a more engaging way to teach and learn poetry.

Fault diagnosis method for oil-immersed transformers integrated digital twin model

To address the problems of low accuracy in fault diagnosis of oil-immersed transformers, poor state perception ability and real-time collaboration during diagnosis feedback, a fault diagnosis method for transformers based on the integration of digital twins is proposed. Firstly, fault sample balance is achieved through Iterative Nearest Neighbor Oversampling (INNOS), Secondly, nine-dimensional ratio features are extracted, and the correlation between dissolved gases in oil and fault types is established. Then, sparse principal component analysis (SPCA) is used for feature fusion and dimensionality reduction. Finally, the Aquila Optimizer (AO) is introduced to optimize the parameters of the Kernel Extreme Learning Machine (KELM), establishing the optimal AO-KELM diagnosis model. The final fault diagnosis accuracy reaches 98.1013%. Combining transformer digital twin models, real-time interaction mapping between physical entities and virtual space is achieved, enabling online diagnosis of transformer faults. Experimental results show that the method proposed in this paper has high diagnostic accuracy and strong stability, providing reference for the intelligent operation and maintenance of transformers.

Monitoring and interactive mapping of illegal environmental activities on the example of Slovakia

Monitoring and interactive mapping of illegal environmental activities on the example of Slovakia

[Translated article] Bibliometric Study of the Advances Made in Clinical Dermatological Research in Spain from 2015 through 2021: Update of the MaIND Project and Interactive Online Map

IntroductionA clinical dermatological research was conducted in Spain from 2005 through 2014 as part of the MaIND project with the provinces or centers with the highest number of published articles. However, a low level of evidence in scientific production was confirmed as the overall result. The aim of this study is to update the Spanish clinical dermatological research in bibliometric terms from 2015 through 2021 with comparisons between both periods of time. Material and methodsWe conducted a bibliometric study to replicate the methodology used in the article to be updated. We included articles whose corresponding authors’ affiliation was a Spanish dermatological center, which met the criteria for clinical research in dermatology, including a level of evidence ≤4. ResultsA total of 1,674 out of the 10,199 articles met the inclusion criteria. An interactive map representing quantitative and qualitative indicators calculated for the 2005-2021 is presented here. In the study period, we found an increasing trend both in the number of published articles (P<.002) and in the mean number of citation-years per article (P<.01). A total of 22 of the articles had a level of evidence >4, with a positive trend towards more articles having a higher level of evidence (P<.03). ACTAS DERMOSIFILOGRÁFICAS still maintains its position as the journal with the highest number of articles received (18%, a total of 302 articles). ConclusionsThe results of this study show that, in Spain, the scientific production of dermatology represents an upward trend in quantity, impact, and level of evidence.

Resolving 3-Dimensional Genomic Landscape of CD4+ T Cells in the Peripheral Blood of Patients with Psoriasis

A precise regulation of gene expression depends on the accuracy of the 3-dimensional (3D) structure of chromatin; however, the effects of the 3D genome on gene expression in psoriasis remain unknown. In this study, we conducted Hi-C and RNA sequencing on CD4+ T cells collected from 5 patients with psoriasis and 3 healthy controls and constructed a comprehensive 3D chromatin interaction map to delineate the genomic hierarchies, including A/B compartments, topologically associated domains, and chromatin loops. Then, the specific superenhancers related to psoriasis were identified by Hi-C and H3K27ac chromatin immunoprecipitation sequencing data. Subsequently, comprehensive analyses were carried out on the differentially expressed genes that are associated with altered topologically associated domains, loops, and superenhancers in psoriasis. Finally, we screened the candidate target genes and examined the potential functional SNP in psoriasis affected by disruptions of the spatial organization. This study provides a comprehensive reference for examining the 3D genome interactions in psoriasis and elucidating the interplay between spatial organization disruption and gene regulation. We hope that our findings can help clarify the mechanisms underlying the pathogenesis of psoriasis and shed light on the role of 3D genomic structure, therefore informing potential therapeutic approaches.

Abstract P364: Chromatin Interactions Between Regulatory Elements Influence Gene Expression in Human iPSC-Derived Endothelial and Vascular Smooth Muscle Cells

Most SNPs associated with blood pressure (BP) are located in noncoding regions of the human genome, where they may regulate gene expression in BP-relevant cell types. However, the mechanisms by which these SNPs influence BP regulation are unclear. To address this, we developed comprehensive epigenomic landscapes in human induced pluripotent stem cell (iPSC)-derived endothelial cells (iECs) and vascular smooth muscle cells (iVSMCs), incorporating DNA methylation analysis (RRBS), transcriptome analysis (RNA-seq), chromatin state profiling (ATAC-seq), and chromatin interaction mapping (Micro-C). We identified 5301, 8916, and 6046 chromatin loops in iECs and 5329, 7598, and 5228 loops in iVSMCs at 4, 8, and 16 kb resolutions (FDR &lt; 0.05) respectively based on the Micro-C analysis. Remarkably, 82.4% and 83.8% of these chromatin contact regions in iECs and iVSMCs, respectively, harbored at least one known regulatory element such as an enhancer, promoter, or transcription factor binding site. Notably, 109 and 119 BP-associated SNPs were found within the chromatin contact regions of iECs and iVSMCs, respectively. We further investigated chromatin contact regions that involved interactions of regulatory elements. In both iECs and iVSMCs, lower methylation levels were observed in chromatin contact regions involving promoter-promoter (PP) and enhancer-promoter (EP) interactions, compared to enhancer-enhancer (EE), enhancer-transcription factor binding site (ET), and promoter-transcription factor binding site (PT) interactions. Additionally, greater chromatin accessibility was observed in chromatin contact regions involving PP and EP interactions. BP-associated SNPs were significantly enriched in chromatin contact regions involving PP and EP interactions. Moreover, genes proximal to chromatin contact regions involving PP or EP interactions exhibited higher expression than those near EE or other regulatory element interactions. These findings offer new insights into how chromatin interactions between regulatory elements define transcriptional states in human endothelial and vascular smooth muscle cells, providing a novel basis for understanding the genetic regulation of BP.

Machine learning unravels inherent structural patterns in Escherichia coli Hi-C matrices and predicts chromosome dynamics.

High dimensional nature of the chromosomal conformation contact map ('Hi-C Map'), even for microscopically small bacterial cell, poses challenges for extracting meaningful information related to its complex organization. Here we first demonstrate that an artificial deep neural network-based machine-learnt (ML) low-dimensional representation of a recently reported Hi-C interaction map of archetypal bacteria Escherichia coli can decode crucial underlying structural pattern. The ML-derived representation of Hi-C map can automatically detect a set of spatially distinct domains across E. coli genome, sharing reminiscences of six putative macro-domains previously posited via recombination assay. Subsequently, a ML-generated model assimilates the intricate relationship between large array of Hi-C-derived chromosomal contact probabilities and respective diffusive dynamics of each individual chromosomal gene and identifies an optimal number of functionally important chromosomal contact-pairs that are majorly responsible for heterogenous, coordinate-dependent sub-diffusive motions of chromosomal loci. Finally, the ML models, trained on wild-type E. coli show-cased its predictive capabilities on mutant bacterial strains, shedding light on the structural and dynamic nuances of ΔMatP30MM and ΔMukBEF22MM chromosomes. Overall our results illuminate the power of ML techniques in unraveling the complex relationship between structure and dynamics of bacterial chromosomal loci, promising meaningful connections between ML-derived insights and biological phenomena.