Navigating geographical disparities: access to obstetric hospitals in maternity care deserts and across the United States.

BACKGROUND: Access to maternity care in the U.S. remains inequitable, impacting over two million women in maternity care "deserts." Living in these areas, exacerbated by hospital closures and workforce shortages, heightens the risks of pregnancy-related complications, particularly in rural regions. This study investigates travel distances and time to obstetric hospitals, emphasizing disparities faced by those in maternity care deserts and rural areas, while also exploring variances across races and ethnicities. METHODS: The research adopted a retrospective secondary data analysis, utilizing the American Hospital Association and Centers for Medicaid and Medicare Provider of Services Files to classify obstetric hospitals. The study population included census tract estimates of birthing individuals sourced from the U.S. Census Bureau's 2017-2021 American Community Survey. Using ArcGIS Pro Network Analyst, drive time and distance calculations to the nearest obstetric hospital were conducted. Furthermore, Hot Spot Analysis was employed to identify areas displaying significant spatial clusters of high and low travel distances. RESULTS: The mean travel distance and time to the nearest obstetric facility was 8.3 miles and 14.1 minutes. The mean travel distance for maternity care deserts and rural counties was 28.1 and 17.3 miles, respectively. While birthing people living in rural maternity care deserts had the highest average travel distance overall (33.4 miles), those living in urban maternity care deserts also experienced inequities in travel distance (25.0 miles). States with hotspots indicating significantly higher travel distances included: Montana, North Dakota, South Dakota, and Nebraska. Census tracts where the predominant race is American Indian/Alaska Native (AIAN) had the highest travel distance and time compared to those of all other predominant races/ethnicities. CONCLUSIONS: Our study revealed significant disparities in obstetric hospital access, especially affecting birthing individuals in maternity care deserts, rural counties, and communities predominantly composed of AIAN individuals, resulting in extended travel distances and times. To rectify these inequities, sustained investment in the obstetric workforce and implementation of innovative programs are imperative, specifically targeting improved access in maternity care deserts as a priority area within healthcare policy and practice.

Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study.

In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. This study aimed to investigate molecular and spatial epidemiology of TB in two mountainous, rural counties of Zhejiang Province, China, from 2015 to 2021, to elucidate the recent transmission and drug-resistance profiles. The predominant Lineage 2 (L2) Beijing family accounted for 80.1% of total 532 sequenced Mycobacterium tuberculosis (Mtb) strains, showing consistent prevalence over seven years. Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.

Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin.

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

Spatial analysis of leachate penetration at Lemna dumpsite, Calabar: Implications for sustainable waste management in Cross River State.

This study rigorously investigated the spatial analysis of leachate penetration at Lemna dumpsite, located in Calabar, Cross River State, Nigeria. Purposeful soil sampling, performed at specific intervals (5 m, 25 m, and 50 m) along the Electrical Resistivity profile line within the dumpsite, was augmented by water sample collection from five boreholes near Lemna dumpsite. Utilizing Electrical Resistivity Tomography (ERT) and Vertical Electric Sounding (VES) survey techniques, resistivity data were systematically gathered to comprehensively analyze the Leachate Penetration in the Lemna dumpsite. Laboratory analysis of soil and borehole water quality focused on Benzene, Toluene, Ethylbenzene, and Xylene (BTEX), with paired sample t-tests applied for statistical scrutiny. Analyzing the ERT and VES data employed sophisticated techniques embedded in Resistivity Two Dimension Invasion software and Advanced Geosciences Incorporation Earth Imager software. Substantial disparities (p < 0.05) emerged in the paired sample t-tests for BTEX in soil compared to National Environmental Standard Regulation and Enforcement Agency (NESREA) limits. Similarly, BTEX in borehole water displayed significant differences (p < 0.05) when compared to World Health Organization (WHO) standards, raising alarming concerns about the safety and portability of groundwater in the area. The examination of dumpsite leachate penetration revealed a resistivity anomaly of 8.01 Ωm and an inverse depth of 12.4 m, underscoring profound environmental implications and necessitating immediate remediation efforts. Additionally, Vulnerability and Aquifer Protective Capacity Index (VES) results, with a rating of <0.1, indicated severely compromised aquifer protective capacity, emphasizing the vulnerability of groundwater resources to further contamination. Our study advocates for strategic management, remediation, and monitoring measures to prevent contamination and safeguard water quality in the region.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds.

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3-N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Measuring access to food banks and food pantries: A scoping review of spatial analysis approaches.

Food banks and food pantries are crucial in supporting access to food and addressing food insecurity for millions of people. This scoping review identified eighteen articles that applied spatial analysis approaches to measure access to food banks and food pantries. The review summarizes the methods and primary findings of these studies, and examines how these address different dimensions of food access. Findings suggest that the majority of studies measured the accessibility and availability dimensions of food access, and two addressed accommodation. Through a discussion of these studies' methods and broader literature on food environments, we highlight opportunities to integrate advanced geospatial and mixed methods to support an empirically grounded and broader understanding of food bank and pantry access in future research. This will yield a more holistic picture of food environments and provide practical implications for site selection, resource allocation, and food assistance operations.

Bi-level Graph Learning Unveils Prognosis-Relevant Tumor Microenvironment Patterns from Breast Multiplexed Digital Pathology.

The tumor microenvironment is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. Despite extensive research efforts dedicated to characterizing this complex and heterogeneous environment, considerable challenges persist. In this study, we introduce a data-driven approach for identifying patterns of cell organizations in the tumor microenvironment that are associated with patient prognoses. Our methodology relies on the construction of a bi-level graph model: (i) a cellular graph, which models the intricate tumor microenvironment, and (ii) a population graph that captures inter-patient similarities, given their respective cellular graphs, by means of a soft Weisfeiler-Lehman subtree kernel. This systematic integration of information across different scales enables us to identify patient subgroups exhibiting unique prognoses while unveiling tumor microenvironment patterns that characterize them. We demonstrate our approach in a cohort of breast cancer patients, where the identified tumor microenvironment patterns result in a risk stratification system that provides complementary, new information with respect to alternative standards. Our results, which are validated in a completely independent cohort, allow for new insights into the prognostic implications of the breast tumor microenvironment, and this methodology could be applied to other cancer types more generally.

Temporal trends and space-time distribution of leprosy relapse in Brazil from 2001 to 2021.

BACKGROUND: To analyse the temporal trends and spatiotemporal distribution of leprosy relapse in Brazil from 2001 to 2021. METHODS: An ecological study with a temporal trend approach and space-time analysis of leprosy relapse in Brazil was carried out with data from the Notifiable Diseases Information System. RESULTS: A total of 31 334 patients who experienced leprosy relapse were identified. The number of recurrent cases tended to increase throughout the study period, and this increase was significant among females and in almost all age groups, except for those <15, 50-59 and ≥70 y. Several clusters of high- and low-risk patients were identified across all regions with a heterogeneous distribution. CONCLUSIONS: The burden of relapse showed an increasing trend in some groups and was distributed in all regions.

SpatialCells: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data.

Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.

International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010-2021).

BACKGROUND: International migration is a global phenomenon with significant implications on the health-disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective and the associated factors. METHOD: This was an ecological study of cases of tuberculosis in international migrants in Brazil, between 2010 and 2021. Annual incidence rates were calculated and spatiotemporal scan techniques were used to identify municipalities at risk. Multiple logistic regression was used to identify factors associated with tuberculosis in international migrants. RESULTS: A total of 4037 cases of tuberculosis were reported in Brazil in international migrants. Municipalities at risk for this event were identified using the spatiotemporal scan technique, and a cluster was identified with ITT: +52.01% and ETT: +25.60%. A higher probability of TB infection was identified in municipalities with a TB incidence rate >14.40 cases/100 inhabitants, population >11,042 inhabitants, Gini index >0.49, and illiteracy rate >13.12%. A lower probability was found in municipalities with average per capita household income >BRL 456.43. CONCLUSIONS: It is recommended that health authorities implement monitoring and rigorous follow-up in affected areas to ensure proper diagnosis and treatment completion for international migrants, preventing disease spread to other communities.

Outpatient geriatric health care in the German federal state of Mecklenburg-Western Pomerania: a population-based spatial analysis of claims data.

BACKGROUND: Due to unidentified geriatric needs, elderly patients have a higher risk for developing chronic conditions and acute medical complications. Early geriatric screenings and assessments help to identify geriatric needs. Holistic and coordinated therapeutic approaches addressing those needs maintain the independence of elderly patients and avoid adverse effects. General practitioners are important for the timely identification of geriatric needs. The aims of this study are to examine the spatial distribution of the utilization of outpatient geriatric services in the very rural Federal State of Mecklenburg-Western Pomerania in the Northeast of Germany and to identify regional disparities. METHODS: Geographical analysis and cartographic visualization of the spatial distribution of outpatient geriatric services of patients who are eligible to receive basic geriatric care (BGC) or specialized geriatric care (SGC) were carried out. Claims data of the Association of Statutory Health Insurance Physicians in Mecklenburg-Western Pomerania were analysed on the level of postcode areas for the quarter periods between 01/2014 and 04/2017. A Moran's I analysis was carried out to identify clusters of utilization rates. RESULTS: Of all patients who were eligible for BGC in 2017, 58.3% (n = 129,283/221,654) received at least one BCG service. 77.2% (n = 73,442/95,171) of the patients who were eligible for SGC, received any geriatric service (BGC or SGC). 0.4% (n = 414/95,171) of the patients eligible for SGC, received SGC services. Among the postcode areas in the study region, the proportion of patients who received a basic geriatric assessment ranged from 3.4 to 86.7%. Several regions with statistically significant Clusters of utilization rates were identified. CONCLUSIONS: The widely varying utilization rates and the local segregation of high and low rates indicate that the provision of outpatient geriatric care may depend to a large extent on local structures (e.g., multiprofessional, integrated networks or innovative projects or initiatives). The great overall variation in the provision of BGC services implicates that the identification of geriatric needs in GPs' practices should be more standardized. In order to reduce regional disparities in the provision of BGC and SGC services, innovative solutions and a promotion of specialized geriatric networks or healthcare providers are necessary.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment.

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Spatial distribution of zero-dose children in Ethiopia: evidence for a targeted intervention from a large-scale cross-sectional evaluation survey.

Background: Ethiopia is the fourth leading contributor to the global total of zero-dose children (those who lack the first dose of diphtheria-tetanus-pertussis containing vaccine) and has substantial regional variations in zero-dose children. This study explored the spatial pattern of zero-dose children aged 12-35 months in Ethiopia. Methods: A survey was conducted in pastoralist regions, developing regions, newly-established regions, conflict-affected areas, underserved urban populations, hard-to-reach areas, internally displaced populations, and refugees. Spatial autocorrelation was measured using the Global Moran'sIstatistic. Getis-Ord Gi* statistics was applied to calculate the spatial variability of the high and low prevalence rates of zero-dose children. The spatial interpolation technique was also applied to estimate unknown values that fall between known values. Inverse distance weighting interpolation method was used to predict the risk of zero-dose children. ArcGIS version 10.8 was used for the spatial analysis. Results: A total of 3,646 children aged 12-35 months were included in the study. The spatial distribution of zero-dose children in Ethiopia was non-random (Global Moran'sI = 0.178971, p < 0.001). According to the hotspot analysis, western, eastern and northern parts of Somali and western and central parts of Afar regions had the highest load of zero-dose children (hotspot areas) followed by the Northeastern part of Amhara and southeastern part of Oromia regions. On the other hand, Southern Nations, Nationalities, and Peoples, Sidama, and the Eastern part of the Southwest Ethiopia peoples regions were identified as cold spot areas. The spatial interpolation analysis corresponded with the hotspot analysis results where western and central parts of Afar and western, eastern and northern parts of Somali regions were identified as high-risk areas for zero-dose children. However, Addis Ababa, Dire Dawa, Harari, Southern Nations, Nationalities, and Peoples, Sidama, Southwest Ethiopia Peoples, and parts of Oromia were found to be low-risk areas for zero-dose children. Conclusion: The spatial analysis identified that zero-dose children had a significant spatial variation across the study areas. High clusters of zero-dose children were detected in Afar and Somali regions. Implementing routine and mop-up vaccination campaigns in the identified hotspot areas will help Ethiopia to improve coverage and reduce immunization inequalities.

Analysis of spatial and demographic factors associated with chikungunya in Espírito Santo state, Brazil.

BACKGROUND: Chikungunya (CHIK) emerged in Brazil in 2014 and since then several epidemics have been observed. This study aims to describe the spatial, social and demographic characteristics of individuals affected by CHIK in Espírito Santo state. METHODS: A cross-sectional study was performed using data from individuals with a confirmed diagnosis of CHIK in Espírito Santo state, Brazil, from 2018 to 2020. Monthly incidence was calculated and annual spatial distribution maps were constructed. Statistical analysis using the χ2 test identified associations between disease occurrence and sociodemographic variables. RESULTS: In the period and area analysed, a CHIK epidemic occurred in 2020, with an incidence of 219.8 cases per 100 000 inhabitants. The southern and central regions of Espirito Santo state harboured a risk five times greater than the others in the epidemic region. Females (odds ratio [OR] 1.65 [95% confidence interval {CI} 1.58 to 1.72]), black people (OR 1.22 [95% CI 1.13 to 1.33]), individuals with ≤11 y of education (OR 1.48 [95% CI 1.37 to 1.61]) and the elderly (OR 7.49 [95% CI 6.53 to 8.59]) had a greater risk for the disease. CONCLUSIONS: CHIK stands as an emerging public health problem in Brazil since its introduction in 2014. Espírito Santo suffered a substantial epidemic in 2020, possibly due to outbreaks in neighbouring states. The population at risk should be prioritized in healthcare, considering the morbidity potential of the disease.

Geospatial analysis and prevalence of Schistosoma mansoni and soil-transmitted helminth infections in an endemic area in Eastern Brazilian Amazon.

OBJECTIVES: This study evaluated the occurrence of Schistosoma mansoni and soil-transmitted helminths in an endemic area in the Eastern Brazilian Amazon, analysing prevalence and spatial distribution. METHODS: The study was conducted in four localities of Primavera Municipality, in Pará state. Data was obtained from the Decit 40/2012 project and the participants were divided into five age range categories for evaluation: children, adolescents, young adults, adults and elderly individuals. For the diagnostic tests, Kato-Katz slides were prepared to detect S. mansoni and soil-transmitted helminths eggs. The spatial distribution map and the Kernel Density Estimation were performed to assess the presence and location of infections. RESULTS: Stool samples revealed the presence of hookworms, S. mansoni, Ascaris lumbricoides and Trichuris trichiura eggs. Mono-, bi- and poly-parasitic infections were observed, with a significant prevalence of hookworm monoparasitism. CONCLUSIONS: The high frequency of children infected with soil-transmitted helminths confirms their significance as an ongoing public health problem in the poorest municipalities of Brazil. The Geographic Information System plays a crucial role in environmental surveillance and in the control of epidemics and endemic diseases, enabling accurate assessment and informed decision-making for their control.

From erosion to epidemics: Understanding the overlapping vulnerability of hydrogeomorphic hotspots, malaria affliction, and poverty in Nigeria.

Hydrogeomorphic changes, encompassing erosion, waterlogging, and siltation, disproportionately threaten impoverished rural communities. Yet, they are often marginalized in discussions of disasters. This oversight is especially concerning as vulnerable households with limited healthcare access are most susceptible to related diseases and displacement. However, our current understanding of how these risks intersect remains limited. We explore the complex relationships between hydrogeomorphic hazards, malaria incidence, and poverty in Nigeria. Through spatial analyses we expand traditional boundaries, incorporating factors such as healthcare access, migration patterns, dam locations, demographics, and wealth disparities into a unified framework. Our findings reveal a stark reality: most residents in hydrogeomorphic hotspots live in poverty (earnings per person ≤$1.25/day), face elevated malaria risks (80 % in malaria hotspots), reside near dams (59 %), and struggle with limited healthcare access. Moreover, exposure to hydrogeomorphic hotspots could double by 2080, affecting an estimated 5.8 million Nigerians. This forecast underscores the urgent need for increased support and targeted interventions to protect those living in poverty within these hazardous regions. In shedding light on these dynamics, we expose and emphasise the pressing urgency of the risks borne by the most vulnerable populations residing in these regions-communities often characterised by limited wealth and resilience.

Is entrepreneurship a key factor in the development of European countries? A proposal for an innovation readiness environment (IRE) index.

This study investigates the complex interplay among innovation, research and development (R&D), and entrepreneurship within the context of European nations. The focus of the study is also on the contributory role of tertiary educational institutions in nurturing entrepreneurial activities. To deepen the understanding of these multifaceted relationships and their subsequent impact on regional economies, the research introduces a novel metric termed the Innovation Readiness Environment (IRE) index. This index combines various indicators such as R&D expenditure, patenting rates, firm size, and educational levels, thereby providing a framework for evaluating the innovative capabilities and entrepreneurial success of firms in a given region. Utilization of this index offers policymakers and stakeholders a nuanced understanding of the regional innovation ecosystem, facilitating the identification of both strengths and deficiencies. This, in turn, enables the formulation of targeted policy interventions to enhance both innovation and entrepreneurship. One salient conclusion drawn from this study is the pivotal role of tertiary education in catalysing entrepreneurial ventures. The findings posit that higher levels of entrepreneurial education significantly supplement an individual's likelihood of entrepreneurial success by imparting the requisite skills and knowledge indispensable in a competitive business milieu. Higher education institutions, by fostering an environment conducive to innovation, emerge as critical agents in the cultivation of entrepreneurial acumen and the stimulation of economic expansion. The study further incorporates a spatial analytical framework to elucidate the regional specificities of innovation at the pan-European scale.

The present research examines the interconnected roles of innovation, research and development, and entrepreneurship in European countries, particularly emphasising how higher education contributes to entrepreneurial activity. Through the introduction of the Innovation Readiness Environment (IRE) index, the study provides a structured way to measure various aspects like research spending, patent rates, and educational levels in a region. The IRE index is intended to guide policymakers and other key stakeholders. The index is a tool for comprehensively assessing regional strengths and weaknesses in innovation and entrepreneurship. Furthermore, the study underscores the crucial role of higher education in fostering entrepreneurial skills, thereby enhancing the probability of entrepreneurial success. As a result, it appears that universities are not just places for acquiring knowledge; they serve as incubators for new ideas and start-ups, contributing to broader economic growth.

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging.

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

'Nowhere and no one is safe': spatial analysis of damage to critical civilian infrastructure in the Gaza Strip during the first phase of the Israeli military campaign, 7 October to 22 November 2023.

BACKGROUND: Since the Hamas attacks in Israel on 7 October 2023, the Israeli military has launched an assault in the Gaza Strip, which included over 12,000 targets struck and over 25,000 tons of incendiary munitions used by 2 November 2023. The objectives of this study include: (1) the descriptive and inferential spatial analysis of damage to critical civilian infrastructure (health, education, and water facilities) across the Gaza Strip during the first phase of the military campaign, defined as 7 October to 22 November 2023 and (2) the analysis of damage clustering around critical civilian infrastructure to explore broader questions about Israel's adherence to International Humanitarian Law (IHL). METHODS: We applied multi-temporal coherent change detection on Copernicus Sentinel 1-A Synthetic Aperture Radar (SAR) imagery to detect signals indicative of damage to the built environment through 22 November 2023. Specific locations of health, education, and water facilities were delineated using open-source building footprint and cross-checked with geocoded data from OCHA, OpenStreetMap, and Humanitarian OpenStreetMap Team. We then assessed the retrieval of damage at and with close proximity to sites of health, education, and water infrastructure in addition to designated evacuation corridors and civilian protection zones. The Global Moran's I autocorrelation inference statistic was used to determine whether health, education, and water facility infrastructure damage was spatially random or clustered. RESULTS: During the period under investigation, in the entire Gaza Strip, 60.8% (n = 59) of health, 68.2% (n = 324) of education, and 42.1% (n = 64) of water facilities sustained infrastructure damage. Furthermore, 35.1% (n = 34) of health, 40.2% (n = 191) of education, and 36.8% (n = 56) of water facilities were functionally destroyed. Applying the Global Moran's I spatial inference statistic to facilities demonstrated a high degree of damage clustering for all three types of critical civilian infrastructure, with Z-scores indicating < 1% likelihood of cluster damage occurring by random chance. CONCLUSION: Spatial statistical analysis suggests widespread damage to critical civilian infrastructure that should have been provided protection under IHL. These findings raise serious allegations about the violation of IHL, especially in light of Israeli officials' statements explicitly inciting violence and displacement and multiple widely reported acts of collective punishment.

The risk of contact between visitors and Borrelia burgdorferi-infected ticks is associated with fine-scale landscape features in a southeastern Canadian nature park.

BACKGROUND: Infectious diseases are emerging across temperate regions of the world, and, for some, links have been made between landscapes and emergence dynamics. For tick-borne diseases, public parks may be important exposure sites for people living in urbanized areas of North America and Europe. In most cases, we know more about the ecological processes that determine the hazard posed by ticks as disease vectors than we do about how human population exposure varies in urban natural parks. METHODS: In this study, infrared counters were used to monitor visitor use of a public natural park in southern Quebec, Canada. A risk index representing the probability of encounters between humans and infected vectors was constructed. This was done by combining the intensity of visitor trail use and the density of infected nymphs obtained from field surveillance. Patterns of risk were examined using spatial cluster analysis. Digital forest data and park infrastructure data were then integrated using spatially explicit models to test whether encounter risk levels and its components vary with forest fragmentation indicators and proximity to park infrastructure. RESULTS: Results suggest that, even at a very fine scales, certain landscape features and infrastructure can be predictors of risk levels. Both visitors and Borrelia burgdorferi-infected ticks concentrated in areas where forest cover was dominant, so there was a positive association between forest cover and the risk index. However, there were no associations between indicators of forest fragmentation and risk levels. Some high-risk clusters contributed disproportionately to the risk distribution in the park relative to their size. There were also two high-risk periods, one in early summer coinciding with peak nymphal activity, and one in early fall when park visitation was highest. CONCLUSIONS: Here, we demonstrate the importance of integrating indicators of human behaviour visitation with tick distribution data to characterize risk patterns for tick-borne diseases in public natural areas. Indeed, understanding the environmental determinants of human-tick interactions will allow organisations to deploy more effective risk reduction interventions targeted at key locations and times, and improve the management of public health risks associated with tick-borne diseases in public spaces.