Spatial Analysis Research Articles

Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman

Accurately evaluating drought and its effects on the natural environment is difficult in regions with limited climate monitoring stations, particularly in the hyper-arid region of the Sultanate of Oman. Rising global temperatures and increasing incidences of insufficient precipitation have turned drought into a major natural disaster worldwide. In Oman, drought constitutes a major threat to food security. In this study, drought indices (DIs), such as temperature condition index (TCI), vegetation condition index (VCI), and vegetation health index (VHI), which integrate data on drought streamflow, were applied using moderate resolution imaging spectroradiometer (MODIS) data and the Google Earth Engine (GEE) platform to monitor agricultural drought and assess the drought risks using the drought hazard index (DHI) during the period of 2001–2023. This approach allowed us to explore the spatial and temporal complexities of drought patterns in the Najd region. As a result, the detailed analysis of the TCI values exhibited temporal variations over the study period, with notable minimum values observed in specific years (2001, 2005, 2009, 2010, 2014, 2015, 2016, 2017, 2019, 2020, and 2021), and there was a discernible trend of increasing temperatures from 2014 to 2023 compared to earlier years. According to the VCI index, several years, including 2001, 2003, 2006, 2008, 2009, 2013, 2015, 2016, 2017, 2018, 2020, 2021, 2022, and 2023, were characterized by mild drought conditions. Except for 2005 and 2007, all studied years were classified as moderate drought years based on the VHI index. The Pearson correlation coefficient analysis (PCA) was utilized to observe the correlation between DIs, and a high positive correlation between VHI and VCI (0.829, p < 0.01) was found. Based on DHI index spatial analysis, the northern regions of the study area faced the most severe drought hazards, with severity gradually diminishing towards the south and east, and approximately 44% of the total area fell under moderate drought risk, while the remaining 56% was classified as facing very severe drought risk. This study emphasizes the importance of continued monitoring, proactive measures, and effective adaptation strategies to address the heightened risk of drought and its impacts on local ecosystems and communities.

The spatial-temporal distribution of hepatitis B virus infection in China,2006–2018

ObjectivesHepatitis B is a liver disease caused by Hepatitis B virus (HBV) infection and is highly prevalent in China. To better understand the epidemiological characteristics of hepatitis B in China and develop effective disease control strategies, we employed temporal and spatial statistical methods.MethodsWe obtained HBV incidence data from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention for the years 2006 to 2018. Using Geographic Information System (GIS) and SaTScan scanning technology, we conducted spatial autocorrelation analysis and spatiotemporal scan analysis to create a map and visualize the distribution of hepatitis B incidence.ResultsWhile hepatitis B incidence rebounded in 2011 and 2017, the overall incidence in China decreased.In the trend analysis by item, the incidence varies from high to low. The global spatial autocorrelation analysis revealed a clustered distribution, and the Moran index analysis of spatial autocorrelation within local regions identified five provinces as H-H clusters (hot spots), while one province was an L-L cluster (cold spot). Spatial scan analysis identified 11 significant spatial clusters.ConclusionsWe found significant clustering in the spatial distribution of hepatitis B incidence and positive spatial correlation of hepatitis B incidence in China. We also identified high-risk times and regional clusters of hepatitis B incidence.

Dominant role of grazing and snow cover variability on vegetation shifts in the drylands of Kazakhstan

Decomposing the responses of ecosystem structure and function in drylands to changes in human-environmental forcing is a pressing challenge. Though trend detection studies are extensive, these studies often fail to attribute them to potential spatiotemporal drivers. Most attribution studies use a single empirical model or a causal graph that cannot be generalized or extrapolated to larger scales or account for spatial changes and multiple independent processes. Here, we proposed and tested a multi-stage, multi-model framework that detects vegetation trends and attributes them to ten independent social-environmental system (SES) drivers in Kazakhstan (KZ). The time series segmented residual trend analysis showed that 45.71% of KZ experienced vegetation degradation, with land use change as the predominant contributor (22.54%; 0.54 million km2), followed by climate change and climate variability. Pixel-wise fitted Granger Causality and random forest models revealed that sheep & goat density and snow cover had dominant negative and positive impacts on vegetation in degraded areas, respectively. Overall, we attribute vegetation changes to SES driver impacts for 19.81% of KZ (out of 2.39 million km2). The identified vegetation degradation hotspots from this study will help identify locations where restoration projects could have a greater impact and achieve land degradation neutrality in KZ.

Multi-dimensional equilibrium optimal allocation of water resources in Beijing-Tianjin-Hebei region through spatial association network analysis

The rapid social and economic development has led to problems such as over-exploitation of water resources, strong demand for physical water resources, and disequilibrium of water resources load. Based on the current situation of the water resources system in Beijing-Tianjin-Hebei region, this study proposed an input–output analysis-assessment-prediction-optimization framework. A water resources dissipation environment extended multi-regional input–output model was established, and the spatial equilibrium of water resources load was evaluated comprehensively. Furthermore, a multi-dimensional spatial equilibrium optimal allocation for water resources was built to identify key nodes and sectors. The primary findings were as follows: (1) Shijiazhuang and Tangshan were the main cities with net virtual water outflow, while Beijing and Baoding were the primary recipients of net virtual water inflow; (2) The overall score for the spatial equilibrium assessment of water resource load was low, with dimension scores predominantly ranging between 0.2 and 0.6; (3) The key transfer nodes were predominantly concentrated on the “outflow from Shijiazhuang” and the “inflow to Cangzhou and Langfang” nodes. This research conducted an in-depth exploration of the direction of water resource transfers, the actual stress conditions, and the spatial equilibrium of water resources within the Beijing-Tianjin-Hebei region. Finally, the future adjustment strategy for water-intensive industries at the urban agglomeration scale was obtained.

Assessment of Land Capability and Zoning for Sustainable Urban Development in Ambon City

The optimization strategy replaces ability-useful land with conservation-source power land, which may help with problem degradation. Investigate this to determine the level of land ability and the function area designation for good protection and cultivation in the Satuan Wilayah Pengembangan (SWP). The research method is descriptive and quantitative, with stepwise data collection and processing. Data collection is carried out through studies and literature from several agencies. Temporary spatial data analysis was conducted using Geographic Information System (GIS) software. The research findings underscore a significant aspect regarding land analysis, specifically about allocating areas for settlement purposes. The documented 3687.35 hectares identified as suitable for settlement development, alongside the approximately 11755.27 hectares allocated as buffer zones, highlight a limited portion of land deemed suitable for urban expansion within the studied region. This observation underscores the challenge of finding suitable and adequate spaces for urban development initiatives in Ambon City. Identifying such a confined area underscores the need for strategic urban planning that considers land constraints, such as the predominantly hilly terrain, to ensure balanced development, efficient land use, and the preservation of environmental integrity. Efforts toward optimizing these available areas for urban growth while concurrently focusing on conservation and ecological sustainability become imperative for Ambon City's future urban development trajectory. They created a barrier to physical land where hilly areas dominate the characteristics of the Ambon City area

The Potential of Immunotherapy for SMARCA4-Deficient Undifferentiated Uterine Sarcoma (SDUS).

(1) Background: SMARCA4-deficient undifferentiated uterine sarcoma (SDUS) is a rare and aggressive cancer that urgently requires novel therapeutic strategies. Despite the proven efficacy of immunotherapy in various cancer types, its application in SDUS remains largely unexplored. This study aims to investigate the immune microenvironment of SDUS to evaluate the feasibility of utilizing immunotherapy. (2) Methods: Multiplex immunofluorescence (mIF) was employed to examine the immune microenvironment in two cases of SDUS in comparison to other subtypes of endometrial stromal sarcomas (ESSs). This research involved a comprehensive evaluation of immune cell infiltration, cellular interactions, and spatial organization within the tumor immune microenvironment (TiME). Statistical analysis was performed to assess differences in immune cell densities and interactions between SDUS and other ESSs. (3) Results: SDUS exhibited a significantly higher density of cytotoxic T lymphocytes (CTLs), T helper (Th) cells, B cells, and macrophages compared to other ESSs. Notable cellular interactions included Th-CTL and Th-B cell interactions, which were more prominent in SDUS. The spatial analysis revealed distinct immune niches characterized by lymphocyte aggregation and a vascular-rich environment, suggesting an active and engaged immune microenvironment in SDUS. (4) Conclusions: The results suggest that SDUS exhibits a highly immunogenic TiME, characterized by substantial lymphocyte infiltration and dynamic cellular interactions. These findings highlight the potential of immunotherapy as an effective treatment approach for SDUS. However, given the small number of samples evaluated, these conclusions should be drawn with caution. This study underscores the importance of additional investigation into immune-targeted therapies for this challenging cancer subtype, with a larger sample size to validate and expand upon these preliminary findings.

What is the actual composition of specific land cover? An evaluation of the accuracy at a national scale – Remote sensing in comparison to topographic land cover

Satellite imagery allows us to capture and collect land cover information for increasingly large areas. This allows us to represent current land cover on maps in a simple and standardized way; however, any land cover determined in this way is subject to some algorithmic uncertainty. This paper aims, for the first time, to indicate the magnitude of this uncertainty through the empirical probability distribution of a given land cover at a given location. By analyzing 3 data sources, i.e. the Corine Land Cover map, the POLSA land cover map and the classic map - the BDOT10k database of topographic objects. Empirical distributions of the occurrence of land cover class data in areas with a given land use on a topographic map were determined. The work was carried out on a large scale, i.e. on the maximum possible sample for Poland, i.e. on the area of the whole country. This makes it possible to introduce and quantify uncertainties. Spatial analyses were carried out using satellite-based methods to determine land cover or using a topographic map. This work and its results will be useful to all users who want to assess the occurrence of a phenomenon in a given area, taking into account the uncertainty of the land cover, and thus obtain more accurate and reliable results. It also provides, for the first time, a methodology for verifying such map correspondences, which can be replicated in work by other researchers, using the confusion matrix and as evaluation metrics the true positive rate (TPR) and weighted accuracy have been adopted. The paper proposes a link between land cover classes in all databases. It was shown that the TPR for BDOT10k was higher than 50% only with CLC Level 1 (72.0%) and POLSA Land Cover (61%), while the TPR for RS classes for each remote sensing data was always higher than 60% with BDOT10k. The class with the highest remote sensing classes was related to water, especially marine (92.0% for POLSA and 85.3% for CLC level 3), arable land (98% for POLSA, lowest for CLC level 3 (80%), and forests (coniferous POLSA – 89%, CLC level 1 and 2–85%), while low values were obtained for wetlands, peatbogs. The authors do not state which land cover approach is better, as each may have multiple uses, but the values presented in this work must raise awareness of uncertainties in land cover and critical implementation in decision-making processes for multiple areas of human activity. The study provides ready-to-use values of the probability of a given land cover class being present on a topographic map, given that remote sensing has classified it as such. These functions can also be used in reverse, to determine the probability of a given land cover class being present in remote sensing, given that a specific class has been identified on a topographic map. The results of the consistency assessment, with the composition structure, can be used by a wide range of users, including public administration, land managers, land architects, public services, academia and individuals.

Spatial analysis and assessment of soil erosion in the southern Western Ghats region in India.

Soil erosion is expected to worsen in the future as a result of climate change, growing population demands, improper land use, and excessive exploitation of natural resources in India. Due to the growing population and changes in land use, it has become increasingly crucial to map and quantitatively assess soil for the purpose of sustainable agricultural usage and planning conservation efforts. The problem of soil erosion is mainly on steeper slopes with intense rainfall in parts of Western Ghats. The 20.17% of geographical area have been converted into wasteland due to soil erosion. The Revised Universal Soil Loss Equation (RUSLE) is a highly prevalent and effective technique utilized for estimating soil loss in order to facilitate the planning of erosion control measures. Despite the fact that RUSLE is accurately estimate sediment yields from gully erosion, it is an effective tool in estimating sheet and rill erosions losses from diverse land uses like agricultural to construction sites. The current study is mainly about combining the RUSLE model with GIS (Geographic Information System) to find out how much soil is being lost, particularly in Noyyal and Sanganur watersheds which is located in Coimbatore district of Tamil Nadu, India. This analysis is based on the soil order, with a significant proportion of alfisols and inceptisols being considered. The obtained outcome is contrasted with the established soil loss tolerance threshold, leading to the identification of the areas with the highest susceptibility to erosion. Within the narrower and more inclined section of the watershed, yearly soil loss scales from 0 to 5455 tonnes/ha/year, with an average annual loss of soil of 2.44 tonnes/ha. The severe soil erosion of 100 to 5455 tonnes/ha/year is found along the steep and greater slope length. The generated soil map was classified into six categories: very slight, slight, moderate, high, severe, and very severe. These classifications, respectively, occupied 6.23%, 14.88%, 10.56%, 15.70%, 7.73%, and 6.63% of the basin area. Based on the results of cross-validation, the estimated result of the present study was found to be very high compared to past studies conducted 0 to 368.12 tonnes/ha/year especially in very severe erosion zones. But very slight to severe erosion zones nearly matched with same level of soil loss. To protect the soil in the study area from erosion, more specific actions should be taken. These include micro-catchment, broad bed furrows, up-and-down farming, soil amendment with coconut coir pith composition, streambank stabilization with vegetation, and micro-water harvesting with abandoned well recharge. These actions should be carried out over time to make sure to work.

Analysis of the Impact of Urban Infrastructure on Urbanization Processes at Different Levels from a Spatiotemporal Perspective

A comprehensive understanding of the heterogeneity of urbanization development at different levels and its influencing factors is crucial for promoting global urbanization and advancing China’s new urbanization. Using indicators related to urbanization development, a multidimensional index system was constructed based on five dimensions: population, economy, space, society, and ecology. Employing methods such as the Mann–Kendall test, Sen’s trend analysis, multiple linear regression, and spatial autocorrelation analysis, the spatiotemporal evolution characteristics of urbanization from 2000 to 2019 were analyzed comprehensively at national, economic zone, provincial, and prefectural city scales. The results indicate the following. (1) From 2000 to 2019, urbanization levels at all levels showed an overall upward trend, with the national urbanization rate increasing most rapidly at 5.39%. (2) Trend analysis reveals rapid and significant growth trends in urbanization at the national and economic zone scales, while urban-level changes exhibit greater diversity and spatiotemporal heterogeneity. (3) Spatial distribution patterns show that urbanization levels in the eastern coastal economic zones are significantly higher than those in the northeastern economic zones, highlighting pronounced regional disparities in development and agglomeration effects in economically advanced regions and provinces. (4) Regression analysis demonstrates that spatial urbanization significantly influences urbanization development in China, with urban infrastructure playing a crucial role across different levels.

Spatial mapping of greenhouse gases using a UAV monitoring platform over a megacity in China

Urban environments are recognized as main anthropogenic contributors to greenhouse gas (GHG) emissions, characterized by unevenly distributed emission sources over the urban environments. However, spatial GHG distributions in urban regions are typically obtained through monitoring at only a limited number of locations, or through model studies, which can lead to incomplete insights into the heterogeneity in the spatial distribution of GHGs. To address such information gap and to evaluate the spatial representation of a planned GHG monitoring network, a custom-developed atmospheric sampler was deployed on a UAV platform in this study to map the CO2 and CH4 mixing ratios in the atmosphere over Zhengzhou in central China, a megacity of nearly 13 million people. The aerial survey was conducted along the main roads at an altitude of 150 m above ground, covering a total distance of 170 km from the city center to the suburbs. The spatial distributions of CO2 and CH4 mixing ratios in Zhengzhou exhibited distinct heterogeneities, with average mixing ratios of CO2 and CH4 at 439.2 ± 10.8 ppm and 2.12 ± 0.04 ppm, respectively. A spatial autocorrelation analysis was performed on the measured GHG mixing ratios across the city, revealing a spatial correlation range of approximately 2 km for both CO2 and CH4 in the urban area. Such a spatial autocorrelation distance suggests that the urban GHG monitoring network designed for emission inversion purposes need to have a spatial resolution of 4 km to characterize the spatial heterogeneities in the GHGs. This UAV-based measurement approach demonstrates its capability to monitor GHG mixing ratios across urban landscapes, providing valuable insights for GHG monitoring network design.

Spatiotemporal Evolution and Spatial Analysis of Ecological Environmental Quality in the Longyangxia to Lijiaxia Basin in China Based on GEE.

The upper reaches of the Yellow River are critical ecological barriers within the Yellow River Basin (YRB) that are crucial for source conservation. However, environmental challenges in this area, from Longyangxia to Lijiaxia, have emerged in recent years. To assess the ecological environment quality (EEQ) evolution from 1991 to 2021, we utilized remote sensing ecological indices (RSEIs) on the Google Earth Engine (GEE) platform. Spatial autocorrelation and heterogeneity impacting EEQ changes were examined. The results of this study show that the mean value of the RSEIs fluctuated over time (1991: 0.70, 1996: 0.77, 2001: 0.67, 2006: 0.71, 2011: 0.68, 2016: 0.65, and 2021: 0.66) showing an upward, downward, and then upward trend. The mean values of the overall RSEI are all at 0.65 and above. Most regions showed no significant EEQ change during 1991-2021 (68.59%, 59.23%, and 55.78%, respectively). Global Moran's I values (1991-2021) ranged from 0.627 to 0.412, indicating significant positive correlation between EEQ and spatial clustering, and the LISA clustering map (1991-2021) shows that the area near Longyangxia Reservoir shows a pattern of aggregation, dispersion, and then aggregation again. The factor detection results showed that heat was the most influential factor, and the interaction detection results showed that greenness and heat had a significant effect on regional ecosystem distribution. Our study integrates spatial autocorrelation and spatial heterogeneity and combines them with reality to provide an in-depth discussion and analysis of the Longyangxia to Lijiaxia Basin. These findings offer guidance for ecological governance, vegetation restoration, monitoring, and safeguarding the upper Yellow River's ecological integrity.

Post-occupancy evaluation for tactical urbanism interventions through placemaking model: two case studies from the “Piazze Aperte” program in Milan

ABSTRACT This research examines whether tactical urbanism is capable of generating successful public places based on key placemaking principles. Drawing from established evaluation models, a new model is designed and adapted to the tactical urbanism interventions. The proposed model consists of six principal qualities and 22 variables that are evaluated through a mixed-methods approach. To test its effectiveness, two of the public spaces of the “Piazze Aperte” program in Milan were analyzed, allowing for a comprehensive evaluation of their post-occupancy in providing an inclusive, social, and functional place. The analysis is built on several tools including visual observations, in-depth interviews, and GIS spatial analysis mapping. The findings include the identification of best practices for tactical urbanism as well as limitations and areas for improvement. Lastly, a reflection on the post-occupancy status of the case studies towards the inclusion of community and stakeholders in future planning processes of the “Piazze Aperte” program.

Effect of tumor-immune microenvironment (TIME) on disparate ascending (A) and descending (D) subtypes of nasopharyngeal carcinoma (NPC).

145 Background: Endemic NPC is invariably linked to Epstein-Barr virus infection, and often presents as locoregionally-advanced (LA-) disease. Nonetheless, it is acknowledged that LA-NPC is clinically heterogeneous, with disparate clinical presentations of ascending (A) and descending (D) subtypes that are characterized by T3-4N0-1 and T1-2N2-3 disease, respectively. Here, we investigated the TIME between these distinct NPC phenotypes using whole transcriptome sequencing and digital pathology. Methods: We utilized a cohort of 111 patients with NPC from 2 institutions – NCCS (n=68) and JXCH (n=43) as test and validation datasets, respectively. Whole transcriptome profiling using RNAseq (Illumina, CA) was performed in the NCCS cohort, while spatial analyses of hematoxylin and eosin-stained whole slide images (WSIs) were undertaken in the NCCS cohort (35 A- and 33 D-subtypes), and validated in the JXCH cohort (26 A- and 17 D-subtypes). A customized pipeline was developed to analyze the spatial relationships between tumor-rich and immune-rich regions (tiles) within the WSIs. Mean distances between each tumor-rich and its nearest immune-rich tiles were computed for each WSI. Highest and lowest quartiles of the mean distances in the test cohort were used as thresholds to classify NPC tumors into 3 immune classes of differing immune cell density. Results: Transcriptomic profiling revealed an enrichment of immune-related genesets and differentially expressed genes in D- relative to A-subtype tumors. This corresponded to observations of higher overall immune, T and B cell scores in D- than A-subtypes by deconvolution analyses (ESTIMATE and CIBERSORT). Through spatial analyses of our WSIs, we defined three immune classes – immune-dense, -sparse, and -desert, which corresponded to mean distances of <88 μm, 88-208 μm, and >208 μm between tumour- to immune-rich tiles, respectively. D-subtype NPC had significantly more immune-rich regions compared with A-subtypes in both NCCS and JXCH cohorts ( P=0.02 [NCCS]; P=0.01 [JXCH]). This corresponded to shorter median distances between tumor-rich to immune-rich tiles in D- than A-subtypes (103 μm vs 200 μm, P=0.01 [NCCS]; 123 μm vs250 μm, P=0.01 [JXCH]). Based on our novel spatial-based classification, we observed a higher proportion of immune dense tumors in D- than A-subtypes in the NCCS cohort, with only 3/33 (9%) D-subtypes being classified as immune desert. Using the same distance thresholds, we derived a consistent trend in the JXCH cohort, where a higher proportion of D-subtypes were classified as immune dense and sparse than A-subtypes (59% vs 31%, P=0.01). Conclusions: Our results support a model where the TIME delineates the biology underpinning the disparate clinical presentations of distinct A- and D-subtypes of LA-NPC.

Tumor-associated macrophage clusters linked to immunotherapy in a pan-cancer census

Transcriptional heterogeneity of tumor-associated macrophages (TAMs) has been investigated in individual cancers, but the extent to which these states transcend tumor types and represent a general feature of cancer remains unclear. We performed pan-cancer single-cell RNA sequencing analysis across nine cancer types and identified distinct monocyte/TAM composition patterns. Using spatial analysis from clinical study tissues, we assessed TAM functions in shaping the tumor microenvironment (TME) and influencing immunotherapy. Two specific TAM clusters (pro-inflammatory and pro-tumor) and four TME subtypes showed distinct immunological features, genomic profiles, immunotherapy responses, and cancer prognosis. Pro-inflammatory TAMs resided in immune-enriched niches with exhausted CD8+ T cells, while pro-tumor TAMs were restricted to niches associated with a T-cell-excluded phenotype and hypoxia. We developed a machine learning model to predict immune checkpoint blockade response by integrating TAMs and clinical data. Our study comprehensively characterizes the common features of TAMs and highlights their interaction with the TME.

Evolution stage identification and spatial pattern analysis of Nitraria tangutorum nebkhas based on Gaofen-2 satellite data

The quantitative extraction and evolution stage identification of the Nitraria tangutorum nebkhas are the basis for the restoration of regional plants and the reconstruction of degraded ecosystems. In this paper, the Nitraria tangutorum nebkha in Dengkou County of China was taken as the research object. Through the spectral and texture information of Gaofen-2 satellite image, the quantitative extraction of Nitraria tangutorum nebkha area and coverage information was completed using methods of gray threshold method, mathematical morphology, FCLSU mixed pixel decomposition, kernel density spatial analysis; the current evolution stage of the Nitraria tangutorum nebkha was identified, and their spatial distribution characteristics were analyzed. The results showed that: (1) The user accuracy and mapping accuracy of Nitraria tangutorum nebkha extracted from Random Forest combined with object-oriented classification method were up to 90.32%. (2) The method proposed can achieve an accuracy of 93.76% in extracting the spatial position of Nitraria tangutorum nebkhas. (3) The evolution of Nitraria tangutorum nebkhas can be divided into three stages: embryonic or developmental stage, stable stage, and declining stage, with a proportion of 60.70%, 20.97%, and 18.33%, respectively; The Nitraria tangutorum nebkhas in the study area is mainly in their embryonic or developmental stage, and the proportion of Nitraria tangutorum nebkhas in the declining stage is also large. It can provide technical and theoretical support for the precise extraction of nebkhas in arid and semi-arid desert areas, the identification of their current evolutionary stages, and the study of their spatial distribution patterns.

Carbon inequality under domestic value chain fragmentation

The division of production leads to the separation of production and consumption, resulting in carbon emissions transfer with trade among regions. Thus, quantifying carbon inequality caused by domestic trade is important for allocating emission-reduction tasks and improving emission-reduction efficiency. Considering domestic value chain (DVC) fragmentation in China, we use multiregional input–output tables to divide products into within-province trade products, traditional trade intermediate/final products, and DVC–related trade products. Then, we examine carbon intensity inequality (CII) under DVC fragmentation and, using Theil index to analyze the contributions of between-province economic differences, within-province trade structures, and related influencing factors to CII. Previous studies have mostly focused on issues related to global value chain fragmentation. We take the lead in exploring CII caused by DVC fragmentation, and for the first time decompose the composition of CII from the perspective of DVC fragmentation. In addition, the national CII is attempted to analyze its contribution at the provincial level for the first time, which is a new improvement and exploration of previous regional research perspectives. The empirical results show that China's CII is on an upward trend, with large changes between 2002 and 2007, and then stabilized between 2007 and 2010 due to the financial crisis, before entering a phase of rapid change after 2012. In terms of regional contribution, between-province inequality is the core to PCII, while within-province inequality is the key to CCII. In terms of province, the changes in between-province inequality are relatively stable at early period. In the middle and late stages, the temporal and spatial changes of PCII and CCII between provinces are obvious with “geographic stickiness” weakening. Specifically, the carbon transfer in the early study period is mostly concentrated in traditional trade products, and the share of carbon transfer in DVC-related trade products later rises significantly from 20.05% in 2002 to 36.32% in 2017, and the value-added transfer rises from 17.09% in 2002 to 27.65% in 2017. In terms of influencing factors, energy intensity remains an important component to CII. In addition, the uncertainties of the data and methodology used in this study are discussed and possible future research directions for expansion are elaborated. Finally, specific policy recommendations for mitigating carbon inequality are presented to inform the development of efficient carbon reduction strategies.

Integrative single-cell RNA-seq and spatial transcriptomics analyses reveal diverse apoptosis-related gene expression profiles in EGFR-mutated lung cancer

In EGFR-mutated lung cancer, the duration of response to tyrosine kinase inhibitors (TKIs) is limited by the development of acquired drug resistance. Despite the crucial role played by apoptosis-related genes in tumor cell survival, how their expression changes as resistance to EGFR-TKIs emerges remains unclear. Here, we conduct a comprehensive analysis of apoptosis-related genes, including BCL-2 and IAP family members, using single-cell RNA sequence (scRNA-seq) and spatial transcriptomics (ST). scRNA-seq of EGFR-mutated lung cancer cell lines captures changes in apoptosis-related gene expression following EGFR-TKI treatment, most notably BCL2L1 upregulation. scRNA-seq of EGFR-mutated lung cancer patient samples also reveals high BCL2L1 expression, specifically in tumor cells, while MCL1 expression is lower in tumors compared to non-tumor cells. ST analysis of specimens from transgenic mice with EGFR-driven lung cancer indicates spatial heterogeneity of tumors and corroborates scRNA-seq findings. Genetic ablation and pharmacological inhibition of BCL2L1/BCL-XL overcome or delay EGFR-TKI resistance. Overall, our findings indicate that BCL2L1/BCL-XL expression is important for tumor cell survival as EGFR-TKI resistance emerges.

Identification of a Novel ECM Remodeling Macrophage Subset in AKI to CKD Transition by Integrative Spatial and Single-Cell Analysis.

The transition from acute kidney injury (AKI) to chronic kidney disease (CKD) is a critical clinical issue. Although previous studies have suggested macrophages as a key player in promoting inflammation and fibrosis during this transition, the heterogeneity and dynamic characterization of macrophages are still poorly understood. Here, we used integrated single-cell RNA sequencing and spatial transcriptomic to characterize the spatiotemporal heterogeneity of macrophages in murine AKI-to-CKD model of unilateral ischemia-reperfusion injury. A marked increase in macrophage infiltration at day 1 was followed by a second peak at day 14 post AKI. Spatiotemporal profiling revealed that injured tubules and macrophages co-localized early after AKI, whereas in late chronic stages had spatial proximity to fibroblasts. Further pseudotime analysis revealed two distinct lineages of macrophages in this transition: renal resident macrophages differentiated into the pro-repair subsets, whereas infiltrating monocyte-derived macrophages contributed to chronic inflammation and fibrosis. A novel macrophage subset, extracellular matrix remodeling-associated macrophages (EAMs) originating from monocytes, linked to renal fibrogenesis and communicated with fibroblasts via insulin-like growth factors (IGF) signalling. In sum, our study identified the spatiotemporal dynamics of macrophage heterogeneity with a unique subset of EAMs in AKI-to-CKD transition, which could be a potential therapeutic target for preventing CKD development.

Fractional Anisotropy is a More Sensitive Diagnostic Biomarker Than Mean Kurtosis for Patients with Parkinson Disease with Cognitive Dysfunction: A Diffusional Kurtosis Map Tract-Based Spatial Statistics Study.

There is heterogeneity of white matter damage in Parkinson's disease patients with different cognitive states. Our aim was to find sensitive diffusional kurtosis imaging biomarkers to differentiate the white matter damage pattern of mild cognitive impairment and dementia. Nineteen patients with Parkinson disease with mild cognitive impairment and 18 patients with Parkinson disease with dementia were prospectively enrolled. All participants underwent MR examination with 3D-T1-weighted image and diffusional kurtosis imaging sequences. Demographic data were compared between the 2 groups. Voxelwise statistical analyses of diffusional kurtosis imaging parameters were performed using tract-based spatial statistics. The receiver operator characteristic curve of significantly different metrics was graphed. The correlation of significantly different metrics with global cognitive status was analyzed. Compared with the Parkinson disease with mild cognitive impairment group, the fractional anisotropy and mean kurtosis values decreased in 4 independent clusters in the forceps minor, forceps major, inferior fronto-occipital fasciculus, and the inferior and superior longitudinal fasciculus in patients with Parkinson disease with dementia; the mean diffusivity decreased in 1 cluster in the forceps minor. The fractional anisotropy value in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus would be the diffusional kurtosis imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and patients with Parkinson disease with dementia, with the best diagnostic efficiency of 0.853. The fractional anisotropy values in the forceps minor (β = 84.20, P < .001) and years of education (β = 0.38, P = .014) were positively correlated with the Montreal Cognitive Assessment. The diffusional kurtosis imaging-derived fractional anisotropy and mean kurtosis can detect the different white matter damage patterns of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia. Fractional anisotropy is more sensitive than mean kurtosis in the differential diagnosis; fractional anisotropy derived from diffusional kurtosis imaging could become a promising imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia.

Evaluation of the Harmony of Trade Activities in the Letda Sujono Street Corridor Medan Tembung District Medan City

The development of the population and its supporting facilities has an impact on improving the economy of the people of a city. The Jalan Letda Sujono corridor has experienced significant development of trade and service activities with the location of the area on the border of Medan City with Deli Serdang Regency and the access to the Bandar Selamat Toll Gate. The development of trade and service activities encourages the development of other activities such as housing, public services, commerce, warehousing and industry. This has a big impact on the demands of land provision, the potential for inconsistencies in the use of space, and the disruption of traffic circulation. Inconsistent land use is expected to affect the growth and development of the city which is irregular and directed (urban sprawl). The factor of incompatibility in space utilization in spatial planning is caused by the lack of effective control of space utilization. The Jalan Letda Sujono corridor is planned by the Medan City RDTR as a Trade Sub-Zone zoning which covers 3 (three) planned blocks and there are provisions for activities (zoning regulations) for several activities that are limited by a maximum proportion of 10% of the planned block area. For this reason, it is necessary to conduct a study of the suitability of existing activities with the zoning plan that has been stipulated in the Medan City RDTR as a content of space control in order to realize safe, comfortable and sustainable spatial arrangements. In this study, a qualitative descriptive method with a spatial analysis approach is used to be able to directly compare the existing activity map with the zoning map that has been determined in the Medan City RDTR. The analysis carried out was an analysis of the interpretation of existing activities using satellite images, an analysis of the conformity of the provisions of activities with spatial ovelaping, an analysis of the suitability of activities in excess of 10% proportion, and an analysis of the suitability of activities in the Trade Sub-Zone in the Letda Sujono Street Corridor. The results of this study show that there are 45 types of existing activities consisting of 6,403 persils of activities (polygons). The suitability of activities in the research area was 102.23 Ha (60.84%) and the non-conformity of activities was 65.80 Ha (39.16%). The Plan Block that has been exceeded by activities with a proportion of 10% is Block 17-07-01 (Tembung). In the Trade Sub-Zone in the corridor of Jalan Letda Sujono, it is known that the suitability of its activities covers an area of 19.45 Ha (89.05%) and the non-conformity of its activities covers an area of 2.39 Ha (10.95%). This indicates that the spatial zoning plan has not been fully realized with the existence of Unpermitted Activities (X) in the form of Integrated Schools and the existence of Conditional Activities (B) in the form of Vehicle Pools, Workshops, and Warehouses/Warehouses. The conditional activities are no longer allowed (not allowed) in the Plan Block 17-07-01 (Tembung) because it has exceeded the proportion of activities of 10% of the plan block.