Mapping Platform Research Articles

A national scale web mapping platform for mainstreaming ecosystem services in Greece

This study outlines the conceptualisation and development of a public participation geographic information system (ppGIS) and web GIS (webGIS) platform for hosting, visualizing, and updating ecosystem services (ES) related data at national scale through participatory mapping. The ppGIS/webGIS is developed within the framework of the LIFE-IP 4 Natura, a project has received the most substantial nature-focused funding scheme for Greece approved by the European Commission. One of the project's central goals is the mapping and assessment of ecosystems and their services (MAES) in Greece. This initiative contributes to the implementation of Action 5 of Target 2 of the European Union (EU) Biodiversity Strategy to 2020, following the standard EU MAES guidelines. The LIFE-IP 4 Natura online mapping infrastructure hosts and visualizes spatially explicit maps and information produced earlier in the project at a national level. It also provides a mechanism for updating this baseline information via public participation, thereby fostering increased public awareness of the necessity for ecosystem protection, conservation, and management. Following a multi-stakeholder user requirement analysis, the herein presented ppGIS/webGIS platform is designed and developed. The platform incorporates various geospatial data explorers (GDE), ppGIS services for local and national public participation, geotools and data, visual content representation, and an introductory-level knowledge repository for ES (ES-pedia). An, overview of the platform's preliminary usage is presented, and its potential in promoting the uptake and mainstreaming of the ES concept is discussed.

Adaptive Acquisition and Visualization of Point Cloud Using Airborne LIDAR and Game Engine

The development of digital twin for smart city applications requires real-time monitoring and mapping of urban environments. This work develops a framework of real-time urban mapping using an airborne light detection and ranging (LIDAR) agent and game engine. In order to improve the accuracy and efficiency of data acquisition and utilization, the framework is focused on the following aspects: (1) an optimal navigation strategy using Deep Q-Network (DQN) reinforcement learning, (2) multi-streamed game engines employed in visualizing data of urban environment and training the deep-learning-enabled data acquisition platform, (3) dynamic mesh used to formulate and analyze the captured point-cloud, and (4) a quantitative error analysis for points generated with our experimental aerial mapping platform, and an accuracy analysis of post-processing. Experimental results show that the proposed DQN-enabled navigation strategy, rendering algorithm, and post-processing could enable a game engine to efficiently generate a highly accurate digital twin of an urban environment.

The Effect of a Cultural Landscape Area on Urban Green Spaces: Case Study of Diyarbakir Fortress and Hevsel Gardens

The Diyarbakır Fortress and Hevsel Gardens are an example of combining cultural landscapes and urban green spaces. These types of areas preserve historical and cultural richness while meeting the green and social space needs of modern cities. The aim of this study is to reveal the impact of these two important heritages, which have cultural and historical value, on urban green spaces in the Diyarbakır Sur District. The presence of green areas in the Sur district has been determined in line with this objective. Field observations, Master Development plans, planning annotations, the “management plan”, land registry records, cadastral procedures, urban guidebooks, and digital mapping platforms were employed as methodologies. Inclusive and exclusive quantifications of the designated cultural landscape area were conducted. The study quantitatively reveals the presence of active green areas in two heritage areas intertwined with culture, nature and historical built environment. The fields of heritage and nearby environmental arrangements affect the amount of green space in the Sur district. These landscaping enhancements substantially elevated the per capita functional green space in the district, increasing it from 18.22 square meters to 37.75 square meters. Similarly, they increased the availability of parking spaces, with the per person spacedetermined as 16.64 square meters. This study thus recommends increasing the regulations in buffer zones that reflect the unity of traditional and modern elements, with sustainable approaches that are compatible with ecological balance and planned for the long term

A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations

Travel time estimation accounting for on-the-ground realities between the location where a need for emergency obstetric care (EmOC) arises and the health facility capable of providing EmOC is essential for improving pregnancy outcomes. Current understanding of travel time to care is inadequate in many urban areas of Africa, where short distances obscure long travel times and travel times can vary by time of day and road conditions. Here, we describe a database of travel times to comprehensive EmOC facilities in the 15 most populated extended urban areas of Nigeria. The travel times from cells of approximately 0.6 × 0.6 km to facilities were derived from Google Maps Platform’s internal Directions Application Programming Interface, which incorporates traffic considerations to provide closer-to-reality travel time estimates. Computations were done to the first, second and third nearest public or private facilities. Travel time for eight traffic scenarios (including peak and non-peak periods) and number of facilities within specific time thresholds were estimated. The database offers a plethora of opportunities for research and planning towards improving EmOC accessibility.

Dignified Resources and Coping Strategies During the COVID-19 Pandemic: a Qualitative Study of Racially and Economically Marginalized Communities

IntroductionAmid the spread of the novel coronavirus (COVID-19), racially and economically marginalized communities experienced a disproportionate burden of disease and social consequences (e.g., unemployment, increased exposure). This study seeks to understand strategies that these communities employed to cope with unequal burdens of the pandemic.MethodsWe utilized qualitative data collected between 2020 and 2021 from a mobile mapping platform designed to facilitate real-time, geocoded data collection on individual’s experiences and perceptions of their neighborhoods. Reports were iteratively coded by an academic researcher and community partner. We employed an inductive approach to analysis, which allowed findings to emerge organically without constraint of researcher hypotheses.ResultsA total of 19 respondents (14 under the age of 45, 16 non-White, 15 with less than half a year of emergency savings) provided 236 qualitative reports. Participants described innovative strategies for exchanging resources as a means of informally networking and building community, the importance of tailored programming (e.g., for specific racial/ethnic groups) in fostering belonging and comfort, and the importance of two specific dimensions of services—interactions with service providers and the quality of goods or services—in providing dignified care.DiscussionAmidst exacerbated racial and economic disparities emerging from the COVID-19 pandemic, our study highlights the need for investment in mutual aid, the importance of tailored services and support, and promoting dignity in social services. As other macro-level social stressors become more prevalent as the pandemic continues, these findings can inform how we examine and address them.

A gene expression profile-based approach to screen the occurrence and predisposed host characteristics of drug-induced liver injury: a case study of Psoralea corylifolia Linn.

Drug-induced liver injury (DILI) is one of the most common causes of a drug being withdrawn, and identifying the culprit drugs and the host factors at risk of causing DILI has become a current challenge. Recent studies have found that immune status plays a considerable role in the development of DILI. In this study, DILI-related differentially expressed genes mediated by immunoinflammatory cytokines were obtained from the Gene Expression Omnibus (GEO) database to predict the occurrence of DILI (named the DILI predictive gene set, DILI_PGS), and the predictability of the DILI_PGS was verified using the Connectivity Map (CMap) and LiverTox platforms. The results obtained DILI_PGS from the GEO database could predict 81.25% of liver injury drugs. In addition, the Coexpedia platform was used to predict the DILI_PGS-related characteristics of common host diseases and found that the DILI_PGS mainly involved immune-related diseases and tumor-related diseases. Then, animal models of immune stress (IS) and immunosuppressive (IP) were selected to simulate the immune status of the above diseases. Meanwhile, psoralen, a main component derived from Psoralea corylifolia Linn. with definite hepatotoxicity, was selected as an experimental drug with highly similar molecular fingerprints to three idiosyncratic hepatotoxic drugs (nefazodone, trovafloxacin, and nimesulide) from the same DILI_PGS dataset. The animal experiment results found a single administration of psoralen could significantly induce liver injury in IS mice, while there was no obvious liver function change in IP mice by repeatedly administering the same dose of psoralen, and the potential mechanism of psoralen-induced liver injury in IS mice may be related to regulating the expression of the TNF-related pathway. In conclusion, this study constructed the DILI_PGS with high accuracy to predict the occurrence of DILI and preliminarily identified the characteristics of host factors inducing DILI.

Genetics of vegetarianism: A genome-wide association study.

A substantial body of evidence points to the heritability of dietary preferences. While vegetarianism has been practiced for millennia in various societies, its practitioners remain a small minority of people worldwide, and the role of genetics in choosing a vegetarian diet is not well understood. Dietary choices involve an interplay between the physiologic effects of dietary items, their metabolism, and taste perception, all of which are strongly influenced by genetics. In this study, we used a genome-wide association study (GWAS) to identify loci associated with strict vegetarianism in UK Biobank participants. Comparing 5,324 strict vegetarians to 329,455 controls, we identified one SNP on chromosome 18 that is associated with vegetarianism at the genome-wide significant level (rs72884519, β = -0.11, P = 4.997 x 10-8), and an additional 201 suggestively significant variants. Four genes are associated with rs72884519: TMEM241, RIOK3, NPC1, and RMC1. Using the Functional Mapping and Annotation (FUMA) platform and the Multi-marker Analysis of GenoMic Annotation (MAGMA) tool, we identified 34 genes with a possible role in vegetarianism, 3 of which are GWAS-significant based on gene-level analysis: RIOK3, RMC1, and NPC1. Several of the genes associated with vegetarianism, including TMEM241, NPC1, and RMC1, have important functions in lipid metabolism and brain function, raising the possibility that differences in lipid metabolism and their effects on the brain may underlie the ability to subsist on a vegetarian diet. These results support a role for genetics in choosing a vegetarian diet and open the door to future studies aimed at further elucidating the physiologic pathways involved in vegetarianism.

THE IMPLEMENTATION OF INNOVATIVE TECHNOLOGIES IN TEACHING GEOGRAPHY

This abstract discusses the use of innovative technologies in geography teaching. It highlights how these technologies have transformed the learning experience and deepened students' understanding of the subject. The abstract mentions specific examples such as Geographic Information Systems (GIS), Virtual Reality (VR), Augmented Reality (AR), drones, online mapping platforms, data visualization tools, mobile applications, and online collaborative platforms. It emphasizes the benefits of using these technologies, including enhanced engagement, experiential learning, spatial analysis, and collaboration. The article concludes by noting that the integration of innovative technologies in geography teaching enables students to develop critical thinking, spatial reasoning, and a holistic understanding of the world.

Automated calibration of somatosensory stimulation using reinforcement learning

BackgroundThe identification of the electrical stimulation parameters for neuromodulation is a subject-specific and time-consuming procedure that presently mostly relies on the expertise of the user (e.g., clinician, experimenter, bioengineer). Since the parameters of stimulation change over time (due to displacement of electrodes, skin status, etc.), patients undergo recurrent, long calibration sessions, along with visits to the clinics, which are inefficient and expensive. To address this issue, we developed an automatized calibration system based on reinforcement learning (RL) allowing for accurate and efficient identification of the peripheral nerve stimulation parameters for somatosensory neuroprostheses.MethodsWe developed an RL algorithm to automatically select neurostimulation parameters for restoring sensory feedback with transcutaneous electrical nerve stimulation (TENS). First, the algorithm was trained offline on a dataset comprising 49 subjects. Then, the neurostimulation was then integrated with a graphical user interface (GUI) to create an intuitive AI-based mapping platform enabling the user to autonomously perform the sensation characterization procedure. We assessed the algorithm against the performance of both experienced and naïve and of a brute force algorithm (BFA), on 15 nerves from five subjects. Then, we validated the AI-based platform on six neuropathic nerves affected by distal sensory loss.ResultsOur automatized approach demonstrated the ability to find the optimal values of neurostimulation achieving reliable and comfortable elicited sensations. When compared to alternatives, RL outperformed the naïve and BFA, significantly decreasing the time for mapping and the number of delivered stimulation trains, while improving the overall quality. Furthermore, the RL algorithm showed performance comparable to trained experimenters. Finally, we exploited it successfully for eliciting sensory feedback in neuropathic patients.ConclusionsOur findings demonstrated that the AI-based platform based on a RL algorithm can automatically and efficiently calibrate parameters for somatosensory nerve stimulation. This holds promise to avoid experts’ employment in similar scenarios, thanks to the merging between AI and neurotech. Our RL algorithm has the potential to be used in other neuromodulation fields requiring a mapping process of the stimulation parameters.Trial registration: ClinicalTrial.gov (Identifier: NCT04217005)

Evaluation of Living Environment Quality in Urban Residential Areas under the Concept of Urban Renewal—A Case Study of Binjiang District, Hangzhou, China

As urbanization continues to advance globally, the issue of “urban ailments” has become increasingly prominent. To promptly identify problems arising from urban development, it is crucial to investigate not only the quality of human habitats at the city and regional scales but also the micro-level living environments. Indeed, studying residential living conditions enables the specific problems within urban planning to be unearthed, facilitating timely adjustments for the improvement of urban habitation. However, a precise and objective methodology for accurately measuring the quality of residential living environments is still lacking. In recent years, the urban renewal concept has proven to be proactive in enhancing the living environment quality of residential areas. In this study, we focus on residential areas within Hangzhou’s Binjiang District, China, and integrate diverse datasets including real estate websites, digital mapping platforms, remote sensing imagery, points of interest (POIs), and land-use planning data. By examining and analyzing the urban renewal concept, we establish a comprehensive set of evaluation indicators for the living environment quality in residential areas, including five aspects: residential and environmental factors; transportation and communication; education and culture; lifestyle and leisure; and healthcare and well-being. Subsequently, a holistic assessment of the Binjiang District is conducted. Our research findings demonstrate that in the context of urban renewal, the proposed living environment quality evaluation method, based on multi-source data, exhibits significantly higher practicality and effectiveness. The residential environment in Binjiang District exhibits a spatial pattern with higher quality in the northern regions and lower quality in the southern regions. Across different dimensional layers, the residential and environmental quality shows a higher trend along the river areas and a lower trend in the internal areas, as well as higher quality in newly developed sections compared to older ones. The transportation and communication quality exhibits a decreasing trend radiating from multiple core areas. In other dimensions, there is a concentration of high-quality residential areas in the administrative vicinity and surrounding Binjiang University Town. Hotspot analysis further substantiates a significant spatial correlation between the quality of the living environment and the degree of agglomeration, highlighting a positive relationship between the two factors. This study provides a solid basis for the spatial planning of urban public service facilities and holds significant research and practical value.

Pendampingan Digitalisasi Marketing Desa Kebondalem melalui Aplikasi Google Maps: Upaya Meningkatkan Pengembangan UMKM

This service aims to increase the marketing and reach of Micro, Small and Medium Enterprises (MSMEs), especially in Kebondalem Village, using digital technology, especially the Google Maps platform. MSMEs have an important role in maintaining economic stability and their ability to survive amidst the Corona outbreak in early 2020 is clear proof. During this time, trade and marketing transformed significantly into digital with the use of various technologies. However, MSMEs in Kebondalem Village face challenges in adopting digital marketing. Therefore, using Google Maps is a relevant solution. Google Maps is a platform that allows MSMEs to show their location visually on a map. The app is designed with a simple interface and is easy to use, even by individuals who are not tech savvy. With Google Maps, it is hoped that MSMEs in Kebondalem Village can expand their market coverage. It will be easier for the public to find and contact MSMEs that are registered on Google Maps, providing opportunities for MSMEs to increase sales and survive in this digital era. Thus, it is hoped that this service can make a positive contribution to the development of MSMEs at the local level and the economy

Drug repurposing based on the similarity gene expression signatures to explore for potential indications of quercetin: a case study of multiple sclerosis.

Quercetin (QR) is a natural flavonol compound widely distributed in the plant kingdom with extensive pharmacological effects. To find the potential clinical indications of QR, 156 differentially expressed genes (DEGs) regulated by QR were obtained from the Gene Expression Omnibus database, and new potential pharmacological effects and clinical indications of QR were repurposed by integrating compounds with similar gene perturbation signatures and associated-disease signatures to QR based on the Connectivity Map and Coexpedia platforms. The results suggested QR has mainly potential therapeutic effects on multiple sclerosis (MS), osteoarthritis, type 2 diabetes mellitus, and acute leukemia. Then, MS was selected for subsequent animal experiments as a representative potential indication, and it found that QR significantly delays the onset time of classical MS model animal mice and ameliorates the inflammatory infiltration and demyelination in the central nervous system. Combined with network pharmacology technology, the therapeutic mechanism of QR on MS was further demonstrated to be related to the inhibition of the expression of inflammatory cytokines (TNF-α, IL-6, IL-1β, IFN-γ, IL-17A, and IL-2) related to TNF-α/TNFR1 signaling pathway. In conclusion, this study expanded the clinical indications of QR and preliminarily confirmed the therapeutic effect and potential mechanism of QR on MS.

OBTAINING APPROXIMATIONS FOR RANGE-BASED FREE-NETWORK ADJUSTMENT

Abstract. Airborne and ground mobile mapping platforms are increasingly used in group formations to increase productivity or complement each other in terms of improving observation capacity and efficiency in the surveyed area. Similarly, the navigation of assisted and autonomous vehicles presents a similar problem of sharing a small place where, for example, accurate relative positioning is essential to avoid collisions. Estimating platform relative positions from inter-platform range measurements is important in these applications, as they can provide valuable information to improve individual platform navigation or can potentially detect anomalies in these solutions that could be caused by unintentional or intentional disturbances. Free-network adjustment based on ranges forms the baseline solution to obtain relative positions. The challenge is to provide adequate platform position approximations for the least squares adjustment to achieve both quick convergence and fast execution time. Here we propose a preprocessing method that creates suitable approximations based on range values.

An integrative phenology and climatic suitability model for emerald ash borer.

Decision support models that predict both when and where to expect emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), are needed for the development and implementation of effective management strategies against this major invasive pest of ash (Fraxinus species) in North America and other regions such as Europe. We present a spatialized model of phenology and climatic suitability for EAB for use in the Degree-Days, Risk, and Phenological event mapping (DDRP) platform, which is an open-source decision support tool to help detect, monitor, and manage invasive threats. We evaluated the model using presence records from three geographic regions (China, North America, and Europe) and a phenological dataset consisting primarily of observations from the northeastern and midwestern United States. To demonstrate the model, we produced phenological event maps for a recent year and tested for trends in EAB's phenology and potential distribution over a recent 20-year period. Overall, the model exhibited strong performance. Presence was correctly estimated for over 99% of presence records and predicted dates of adult phenological events corresponded closely with observed dates, with a mean absolute error of ca. 7 days and low estimates of bias. Climate stresses were insufficient to exclude EAB from areas with native Fraxinus species in North America and Europe; however, extreme weather events, climate warming, and an inability for EAB to complete its life cycle may reduce suitability for some areas. Significant trends toward earlier adult emergence over 20 years occurred in only some areas. Near real-time model forecasts for the conterminous United States are available at two websites to provide end-users with decision-support for surveillance and management of this invasive pest. Forecasts of adult emergence and egg hatch are particularly relevant for surveillance and for managing existing populations with pesticide treatments and parasitoid introductions.

Measuring the impact of COVID-19 on heritage sites in the UK using social media data

The COVID-19 pandemic has had a profound impact on almost all aspects of society. Cultural heritage sites, which are deeply intertwined with the tourism industry, are no exception. The direct impacts of the virus on the population, as well as indirect impacts, such as government-mandated measures including social distancing, face coverings, and frequent temporary closures of sites, have greatly impacted visitor experiences at heritage sites. To quantitatively evaluate the impact of these measures from the perspective of visitors, we collected 1.4 millions visitor reviews from the Google Maps platform for 775 heritage sites. We analyzed visiting rates using the number of online reviews as a proxy and adopt state-of-the-art natural language processing techniques to more deeply understand visitor perception of preventive measures put in place to control the spread of COVID-19. Our findings reveal that even if visitor focus on COVID-19 has significantly decreased, there may still be notable difference between actual and expected number of reviews, suggesting that visitor involvement (e.g., number of visitors) for cultural heritage sites, especially urban indoor sites, needs more time to recover. Our findings further show that most comments by visitors to sites were associated with negative sentiment toward restricted access, but recognized the necessity of other safeguarding measures (e.g., social distancing and the requirement for face coverings). Moreover, they exhibited negative sentiment towards staff or other visitors who did not adhere to these measures. We make specific recommendations for heritage sites to adapt to the COVID-19 pandemic and a more general observation that the method used to gather information from online reviews in this paper will be effective in measuring visitor perceptions towards specific aspects of heritage sites, particularly in capturing changes in perception before and after unexpected or disruptive events at heritage sites.

Assessment of Required Patient Travel to Receive Interventional Radiology Services in the Resource-Limited Setting of Tanzania

This study aimed to evaluate the geographic patient profile of a country’s first interventional radiology (IR) service in sub-Saharan Africa. From October 2018 to August 2022, travel time (1,339 patients) and home region (1,184 patients) were recorded from 1,434 patients who underwent IR procedures at Tanzania’s largest referral center. Distances traveled by road were calculated from the administrative capital of each region using a web mapping platform (google.com/maps). The effect of various factors on distance and time traveled were assessed. Patients from all 31 regions in Tanzania underwent IR procedures. The mean and maximum calculated distance traveled by patients were 241.6 km and 1,387 km, respectively (Sk2 = 1.66); 25.0% of patients traveled for over 6 hours for their procedure. Patients traveled furthest for genitourinary procedures (mean = 293.4 km) and least for angioplasty and stent placement (mean = 123.9 km) (P < .001). To increase population access and reduce travel times, geographic data should be used to decentralize services.

Uncovering spatiotemporal pattern of floods with Sentinel-1 synthetic aperture radar in major rice-growing river basins of Tanzania

In Tanzania, 71% of rice is grown in a rainfed lowland rice production ecosystem, primarily in river basins where extreme weather events like floods are frequent. For a six-year period (2017–2022), flood mapping was conducted using Sentinel-1 data in the Google Earth Engine (GEE) platform, utilizing change detection and thresholding methodology. In addition to flood mapping, land use and land cover (LULC) were also analyzed using Sentinel-2 data in GEE, employing the Random Forest (RF) algorithm for classification. The aim was to understand the spatiotemporal extent of floods in two study locations. The resulting flood maps achieved an overall accuracy (OA) greater than 90% for all sites and study years. The findings revealed that agricultural land was the predominant land use/cover in both sub-basins, and floods were widespread in both regions. The study highlighted the interannual variability in flood extent, both spatially and temporally. Specifically, at the Ikwiriri site, floods were more extensive in 2020, covering 54.95% of the cultivated area, while in 2017, the minimum flood extent occurred, affecting 14% of the cultivated area. Similarly, at the Mngeta site, extensive floods were observed in 2020, with floods impacting 5.53% of the cultivated areas, while lower flood extents were observed in 2017, affecting 1.49% of the cultivated areas. Furthermore, the study demonstrated distinct spatiotemporal patterns of floods in both locations, with areas in proximity to rivers and wetlands experiencing more frequent floods. The research showcased the capabilities of the GEE cloud computation platform for flood inundation mapping, emphasizing its potential for enhancing our understanding of rice-producing environments. The generated flood maps can be utilized to guide the selection of areas for trials of flood-tolerant rice varieties and the dissemination of technologies such as flood-tolerant rice varieties, contributing to the resilience of rice farmers in these two floodplains.

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance.

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. 'Diversity Outbred in Australia (DOz)' is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle's contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. ‘Diversity Outbred in Australia (DOz)’ is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle’s contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.

High-resolution photocatalytic mapping of SARS-CoV-2 spike interactions on the cell surface

Identifying virus-host interactions on the cell surface can improve our understanding of viral entry and pathogenesis. SARS-CoV-2, the causative agent of the COVID-19 disease, uses ACE2 as a receptor to enter cells. Yet the full repertoire of cell surface proteins that contribute to viral entry is unknown. We developed a photocatalyst-based viral-host protein microenvironment mapping platform (ViraMap) to probe the molecular neighborhood of the SARS-CoV-2 spike protein on the human cell surface. Application of ViraMap to ACE2-expressing cells captured ACE2, the established co-receptor NRP1, and several novel cell surface proteins. We systematically analyzed the relevance of these candidate proteins to SARS-CoV-2 entry by knockdown and overexpression approaches in pseudovirus and authentic infection models and identified PTGFRN and EFNB1 as bona fide viral entry factors. Our results highlight additional host targets that participate in SARS-CoV-2 infection and showcase ViraMap as a powerful platform for defining viral interactions on the cell surface.