Strong Spatial Association Research Articles

A bayesian shared component spatial modeling approach for identifying the geographic pattern of local associations: a case study of young offenders and violent crimes in Greater Toronto Area

Background settingTraditional spatial or non-spatial regression techniques require individual variables to be defined as dependent and independent variables, often assuming a unidirectional and (global) linear relationship between the variables under study. This research studies the Bayesian shared component spatial (BSCS) modeling as an alternative approach to identifying local associations between two or more variables and their spatial patterns.MethodsThe variables to be studied, young offenders (YO) and violent crimes (VC), are treated as (multiple) outcomes in the BSCS model. Separate non-BSCS models that treat YO as the outcome variable and VC as the independent variable have also been developed. Results are compared in terms of model fit, risk estimates, and identification of hotspot areas.ResultsCompared to the traditional non-BSCS models, the BSCS models fitted the data better and identified a strong spatial association between YO and VC. Using the BSCS technique allowed both the YO and VC to be modeled as outcome variables, assuming common data-generating processes that are influenced by a set of socioeconomic covariates. The BSCS technique offered smooth and easy mapping of the identified association, with the maps displaying the common (shared) and separate (individual) hotspots of YO and VC.ConclusionsThe proposed method can transform existing association analyses from methods requiring inputs as dependent and independent variables to outcome variables only and shift the reliance on regression coefficients to probability risk maps for characterizing (local) associations between the outcomes.

Post-exposure prophylaxis in leprosy (PEOPLE): a cluster randomised trial.

Post-exposure prophylaxis (PEP) using single-dose rifampicin reduces progression from infection with Mycobacterium leprae to leprosy disease. We compared effectiveness of different administration modalities, using a higher (20 mg/kg) dose of rifampicin-single double-dose rifampicin (SDDR)-PEP. We did a cluster randomised study in 16 villages in Madagascar and 48 villages in Comoros. Villages were randomly assigned to four study arms and inhabitants were screened once a year for leprosy, for 4 consecutive years. All permanent residents (no age restriction) were eligible to participate and all identified patients with leprosy were treated with multidrug therapy (SDDR-PEP was provided to asymptomatic contacts aged ≥2 years). Arm 1 was the comparator arm, in which no PEP was provided. In arm 2, SDDR-PEP was provided to household contacts of patients with leprosy, whereas arm 3 extended SDDR-PEP to anyone living within 100 m. In arm 4, SDDR-PEP was offered to household contacts and to anyone living within 100 m and testing positive to anti-phenolic glycolipid-I. The main outcome was the incidence rate ratio (IRR) of leprosy between the comparator arm and each of the intervention arms. We also assessed the individual protective effect of SDDR-PEP and explored spatial associations. This trial is registered with ClinicalTrials.gov, NCT03662022, and is completed. Between Jan 11, 2019, and Jan 16, 2023, we enrolled 109 436 individuals, of whom 95 762 had evaluable follow-up data. Our primary analysis showed a non-significant reduction in leprosy incidence in arm 2 (IRR 0·95), arm 3 (IRR 0·80), and arm 4 (IRR 0·58). After controlling for baseline prevalence, the reduction in arm 3 became stronger and significant (IRR 0·56, p=0·0030). At an individual level SDDR-PEP was also protective with an IRR of 0·55 (p=0·0050). Risk of leprosy was two to four times higher for those living within 75 m of an index patient at baseline. SDDR-PEP appears to protect against leprosy but less than anticipated. Strong spatial associations were observed within 75 m of index patients. Targeted door-to-door screening around index patients complemented by a blanket SDDR-PEP approach will probably have a substantial effect on transmission. European and Developing Countries Clinical Trials Partnership. For the French translation of the abstract see Supplementary Materials section.

Spatiotemporal dynamics of Atlantic reef fishes off the southeastern U.S. coast

AbstractUnderstanding the spatiotemporal dynamics of fish species is a central concern in fish ecology and crucial for guiding management and conservation efforts. We constructed a joint species distribution model (JSDM) to simultaneously estimate the spatiotemporal distributions and densities for 21 reef fish species in the southeastern United States (SEUS). The model separately estimates encounter probability and positive density, and accounts for unobserved spatial and spatiotemporal variation using latent factors, where the correlations among species are induced. We applied the model to video data collected from a large‐scale, fishery independent survey. A clustering method was applied to the results of the JSDM to group species based on spatial and spatiotemporal synchrony in encounter probability and positive density. We found strong spatial associations among most of the reef fish species. However, species did exhibit differences in occupied habitat that varied with latitude and/or depth. Within their area of occupied habitat, almost all the species share similar spatial pattern of average density. However, for some species, annual distributions were less correlated with their expected average distributions perhaps due to differing responses to underlying spatiotemporal drivers. Some species show significant declines in abundance, for example, black sea bass, red porgy, and blueline tilefish, while a small number of species showed evidence of shifts in distribution, for example, black sea bass. The findings suggest that spatiotemporal management strategies may be of limited utility for reducing bycatch in these highly mixed reef fisheries due to high spatial correlations in occupied habitat and spatial patterns in density. Species‐specific responses to environmental change may also influence the spatiotemporal structure of reef assemblages. This work suggests management attention is needed for some of the lesser known species as they are showing declining trends in abundance.

Variable rate phosphorus fertilizer recommendations for rainfed wheat

A uniform application of phosphorus (P) fertilizers to spatially variable soils often results in under-fertilization in low P-localities and over-fertilization in high P-localities. This study aimed to evaluate the variable rate applicability of P fertilizers on a 300-ha sloping landscape under rainfed winter wheat cultivation for over 70 years. The soils were sampled (155 samples) using a random spatial sampling technique based on visual differences in soil color and topographic factors. Plant available soil P content (Pav) and other variables of soil samples were analyzed. The spatial variability of Pav was evaluated and the area was divided into three uniform zones (low, medium, high) for fertilizer P application based on the spatial variation of Pav. The values of Pav showed moderate variablity (CV= 21.3%). The fertilizer recommended by the Ministry of Agriculture and Forestry (MAF) was calculated for five identically-sized sub-regions. The results showed that P fertilizer rates calculated for all five sub-regions based on MAF were identical, suggesting that the MAF was insensitive to spatial variability of Pav in the study soils. Both semivariograms and surface maps of soil properties indicated a strong spatial association between Pav and each of plant available water content (PAWC) and aggregate stability index (ASI), suggesting that yield limitation casued by PAWC should be considered in a variable P-application program in the study area. A more comprehensive study is needed to evaluate the efficiency and cost-benefit economics of variable P application in the study soils.

Assessing the spatial impact of educational attainment on poverty reduction in Thailand

ABSTRACT Using a novel subnational-level dataset of Thailand, the results show a strong spatial association between poverty and educational attainment in Thailand. Provinces with more educated populations are more likely to have lower poverty incidence. In particular, the findings of this study suggest that attainment of tertiary education can significantly affect poverty reduction, while the negligible effects of primary and secondary education could be due to the disparities in education quality. Therefore, the 9-year compulsory education provided by the Thai government might no longer be enough to reduce poverty, and tertiary education might play a more critical role in poverty alleviation.

Local and Regional Dynamics of Native Maize Seed Lot Use by Small-Scale Producers and Their Impact on Transgene Presence in Three Mexican States.

Mexico harbors over 50% of maize's genetic diversity in the Americas. Native maize varieties are actively managed by small-scale producers within a diverse array of cultivation systems. Seed lot use, exchange and admixture has consequences for the in situ conservation of such varieties. Here we analyze native maize seed management dynamics from 906 small-scale producers surveyed in three Mexican states: Mexico City, Oaxaca and Chiapas. Furthermore, we analyze how their management practices can relate to transgene presence, which was experimentally documented for maize samples associated with the applied surveys. Through a data mining approach, we investigated which practices might be related with a higher probability of transgene presence. The variables found to have a strong spatial association with transgene presence were: for Mexico City, maize producers with larger parcels; for Oaxaca, producer's age (43-46 years) and the sale of seed; for Chiapas, the use of agricultural machinery and younger producers (37-43 years). Additionally, transgene presence and frequency within the socioeconomic regions of Oaxaca and Chiapas was analyzed. In Oaxaca, higher transgene frequencies occurred in regions where transgene presence had been previously reported. In Chiapas, the border regions with Guatemala as well as a region where reproduction of improved seed takes place, the highest proportion of positive samples were found. A detailed mapping of regional seed markets and seed exchange sites together with deployment of national and local biosecurity measures, could help prevent the further spread of transgenes into native maize varieties, as well as improve conservation efforts.

Isolated or Colocated? Exploring the Spatio-Temporal Evolution Pattern and Influencing Factors of the Attractiveness of Residential Areas to Restaurants in the Central Urban Area

Catering and urban elements have a strong spatial association. The spatial clustering and dispersal patterns of catering can effectively influence cities’ economic and socio-spatial reconfiguration. This research first introduced the concept of the ARTR (the attractiveness of residential areas to restaurants) and measured its value as well as its spatial and temporal evolutionary patterns using global and local colocation quotients. The DBSCAN algorithm and spatial hot-spot analysis were used to analyze their spatial evolution patterns. On this basis, a multiscale geographically weighted regression (MGWR) model was used to analyze the scale of and spatial variation in the drivers. The results show that (1) Nanjing’s ARTR is at a low level, with the most significant decline in ARTR occurring from 2005 to 2020 for MRs and HRs, while LRs did not significantly respond to urban regeneration. (2) The spatial layout of the ARTR in Nanjing has gradually evolved from a circular structure to a semi-enclosed structure, and the circular structure has continued to expand outward. At the same time, the ARTR for different levels of catering shows a diverse distribution in the margins. (3) Urban expansion and regeneration have led to increasingly negative effects of the clustering level, commercial competition, economic level and neighborhood newness, while the density of the road network has been more stable. (4) The road network density has consistently remained a global influence. Commercial diversity has changed from a local factor to a global factor, while economic and locational factors have strongly spatially non-smooth relationships with the ARTR. The results of this study can provide a basis for a harmonious relationship between catering and residential areas in the context of urban expansion and regeneration.

Identifying where nature-based solutions can offer win-wins for carbon mitigation and biodiversity across knowledge systems

Managing nature-based solutions (NBS) in urban areas for carbon mitigation and biodiversity outcomes is a global policy challenge, yet little is known about how to both assess and weave diverse knowledge systems and values into carbon-biodiversity trade-off assessments. This paper examines the spatial relationships between biophysical and social values for carbon sequestration potential (measured as carbon dioxide, CO2, flux) and biodiversity in Helsinki, Finland, using integrated valuation. The approach combines methods from carbon sequestration modelling, expert scoring approaches to biodiversity assessment and public participation geographic information systems (PPGIS). Results indicate strong spatial associations between biophysical assessment of CO2 flux and biodiversity priorities, and weaker associations between biophysical and social values. Integration of social and biophysical values leads to multiple pathways for protection of NBS to achieve carbon mitigation and biodiversity outcomes, as well as options for the spatial targeting of education and capacity building programs to areas of local concern.

Phosphorus fractions and iron oxides responsible for the variations in the Cd retention capacity in tropical soil aggregates under different cropping patterns.

The environmental behavior of Cd in soil has been widely studied because of its close relationship with food security and soil environmental pollution. In this study, the roles of P fractions and Fe oxides in the retention of Cd in typical tropical soil from five cropping patterns were investigated. Although there was no evident relationship between the Cd adsorption capacity and soil aggregate particle sizes, strong spatial associations of P, Fe, and Cd at the soil aggregates were observed via energy dispersive spectroscopy analysis. Among five cropping patterns, citrus plantations exhibited highest ratios (calculated by pixel area) of P overlapped with Cd (8.61%) and Fe overlapped with Cd (9.53%) in the microaggregates. Furthermore, the random forest model revealed that humic P and labile organic P greatly contributed to the sorptivity of Cd2+ by <0.053mm (13.3%) and 0.25-0.053mm (13.4%) soil aggregates, respectively. Compared with the P fractions in different-sized soil aggregates, the contribution of Fe oxides to the sorption of Cd2+ by soil aggregates was more significant. Amorphous ferric oxide had the most significant contribution to the sorptivity of Cd2+ by <0.053mm (26.0%), 0.25-0.053mm (23.0%), 2.0-0.25mm (25.1%), and >2.0mm (33.9%) soil aggregates.

Automated identification system for ships data as a proxy for marine vessel related stressors

An increasing number of marine conservation initiatives rely on data from Automatic Identification System (AIS) to inform marine vessel traffic associated impact assessments and mitigation policy. However, a considerable proportion of vessel traffic is not captured by AIS in many regions of the world. Here we introduce two complementary techniques for collecting traffic data in the Canadian Salish Sea that rely on optical imagery. Vessel data pulled from imagery captured using a shore-based autonomous camera system (“Photobot”) were used for temporal analyses, and data from imagery collected by the National Aerial Surveillance Program (NASP) were used for spatial analyses. The photobot imagery captured vessel passages through Boundary Pass every minute (Jan–Dec 2017), and NASP data collection occurred opportunistically across most of the Canadian Salish Sea (2017–2018). Based on photobot imagery data, we found that up to 72 % of total vessel passages through Boundary Pass were not broadcasting AIS, and in some vessel categories this proportion was much higher (i.e., 96 %). We fit negative binomial General Linearized Models to our photobot data and found a strong seasonal variation in non-AIS, and a weekend/weekday component that also varied by season (interaction term p < 0.0001). Non-AIS traffic was much higher during the summer (Apr–Sep) and during the weekend (Sat-Sun), reflecting patterns in recreational vessel traffic not obligated to broadcast AIS. Negative binomial General Additive Models based on the NASP data revealed strong spatial associations with distance from shore (up to 10 km) and non-AIS vessel traffic for both summer and winter seasons. There were also associations between non-AIS vessels and marina and anchorage densities, particularly during the winter, which again reflect seasonal recreational vessel traffic patterns. Overall, our GAMs explained 20–37 % of all vessel traffic during the summer and winter, and highlighted subregions where vessel traffic is under represented by AIS.

HYDROGEOLOGY OF FRACTURED AQUIFERS: APPLICATION OF CONSISTENCY INDEXES FOR THE VALIDATION OF GEOSPATIAL MATHEMATICAL MODELS

In hydrogeology, most studies using interpolators seek to estimate water table elevations, contaminant concentrations and aquifer vulnerability. The primary goal of this research was to evaluate which geospatial interpolator best suits six distinct hydrogeological parameters using nine consistency tests. Water wells were selected on a portion of the Serra Geral Fractured Aquifer System in Southern Brazil. This paper tested the Inverse Distance Weighted, Radial Basis Function, Ordinary kriging, Lognormal kriging and Cokriging methods. The results pointed out that the Inverse Distance Weighted showed better performance for the following parameters: potentiometric surface, first fracture flow zone and second fracture flow zone. Discharge, transmissivity, specific capacity and static level showed low consistency levels, greatly increasing the uncertainties associated with mathematical models for such parameters. Deterministic interpolators surpassed the stochastic interpolators in parameter estimates that presented strong spatial dependence and associations with lithostratigraphy and geomorphology. This research can contribute to future work on groundwater management and planning in fractured aquifers, since the use of different interpolation and consistency approaches to analyse and compare different hydrogeological parameters in a fractured aquifer system has not been found in the literature.

Spatial inequalities in education status and its determinants in Pakistan: A district-level modelling in the context of sustainable development Goal-4

Achieving Sustainable Development Goal (SDG)-4 prerequisites quality education provisioning. In this context, we present important insights and references for educational interventions/investments to be tailored to local necessities in Pakistan. Several spatial statistical models such as the Global Moran's I-based spatial autocorrelation, multivariate clustering, and the Cluster and Outlier model are used to explore geographic heterogeneities and patterns. Additionally, significant determinants among several socio-economic, spatio-environmental, and infrastructural variables are identified for education status (EdS) using regression. As a result, a large geographic inequality regarding EdS is found in Pakistan. While a strong spatial association is evident, the districts in northern Punjab are identified as significant hotspots—higher EdS clusters (∼22% of total districts, 95% confidence). Majority of the 44% poorly performing districts belong to Balochistan province (95% confidence). Overall, the educational status in Punjab is higher as compared with other provinces. We find that four out of seven potential factors (i.e., poverty, urbanization, electricity accessibility, and school infrastructure) are statistically significant determinants of EdS. Among these, poverty is the most strongly associated (mean coefficient value −18.848) factor to control EdS. The results have important implications to decision-making for immediate or gradual actions in the context of spatially equitable provisioning of quality education through an informed prioritization (i.e., low performing districts). Based on the findings, while rigorous measures are needed for low performing regions and the identified determinants to improve education status, this study sheds light on the mechanisms to achieve SDG4, consequently promoting human well-being through educating communities.

Interval association of remote sensing ecological index in China based on concept lattice.

The correlation coefficient can calculate paired correlations among different ecological indicators as a whole, but it cannot calculate the specific interval association and the correlation among multiple indicators. This paper proposed an interval association (IA) method of the remote sensing ecological index (RSEI), based on the concept lattice and frequent closed itemset. In the IA method, the ecosystem was viewed as a complex system with a hierarchical structure, and the association among multiple indicators was calculated using the information granulation of RSEI. The interval association support degree (IASD) could measure the association clustering strength of these IA concepts. Calculation of MODIS data compiled by Google Earth Engine (GEE) showed that the IA concepts of RSEI in China were primarily composed of selected middle indicator intervals in 2017. The overall eco-environmental condition in China was general when assessed through IA. The spatial distribution of the remote sensing eco-environment in China displayed strong spatial association clustering. Furthermore, the IA of RSEI focused on the first few concepts with high IASD values.

The spatial association of accessory minerals with biotite in granitic rocks from the South Mountain Batholith, Nova Scotia, Canada

Abstract We use mineral liberation analysis (MLA) to quantify the spatial association of 15,118 grains of accessory apatite, monazite, xenotime, and zircon with essential biotite, and clustered with themselves, in a peraluminous biotite granodiorite from the South Mountain Batholith in Nova Scotia (Canada). A random distribution of accessory minerals demands that the proportion of accessory minerals in contact with biotite is identical to the proportion of biotite in the rock, and the binary touching factor (percentage of accessory mineral touching biotite divided by modal proportion of biotite) would be ~1.00. Instead, the mean binary touching factors for the four accessory minerals in relation to biotite are: apatite (5.06 for 11,168 grains), monazite (4.68 for 857 grains), xenotime (4.36 for 217 grains), and zircon (5.05 for 2876 grains). Shared perimeter factors give similar values. Accessory mineral grains that straddle biotite grain boundaries are larger than completely locked, or completely liberated, accessory grains. Only apatite-monazite clusters are significantly more abundant than expected for random distribution. The high, and statistically significant, binary touching factors and shared perimeter factors suggest a strong physical or chemical control on their spatial association. We evaluate random collisions in magma (synneusis), heterogeneous nucleation processes, induced nucleation in passively enriched boundary layers, and induced nucleation in actively enriched boundary layers to explain the significant touching factors. All processes operate during the crystallization history of the magma, but induced nucleation in passively and actively enriched boundary layers are most likely to explain the strong spatial association of phosphate accessories and zircon with biotite. In addition, at least some of the apatite and zircon may also enter the granitic magma as inclusions in grains of Ostwald-ripened xenocrystic biotite.

A spatial reconnaissance survey for gold exploration in a schist belt

Geological data integration and spatial analysis for structural elucidation are more assertive approaches for reconnaissance scale mineral exploration. In this study, several methods involving Fry analysis, distance correlation analysis, prediction area plots as well as knowledge driven predictive models including TOPSIS, ARAS and MOORA were systematically employed for unravelling the spatial geological attributes related to gold mineralisation. Additionally, statistical validation of knowledge driven predictive models were implemented using the Receiver Operating Characteristic/Area Under Curve analysis (ROC/AUC). The evidence from Fry and distance correlation analysis suggests that gold occurrence within parts of the Malumfashi schist belt of Nigeria is defined by a strong spatial association with the ENE-WSW as well as the NNE-SSW trending structures. The prediction area plot also revealed a robust spatial correlation between mineral occurrence and spatial data related to geological structures. The application of knowledge driven predictive models suggest a high favourability for gold occurrence within the southern, central, and north-eastern parts of the study location, while statistical validation using the ROC/AUC curves suggest a high prediction accuracy greater than 70% for all models. The geospatial analysis for mineral exploration within the Malumfashi area has unveiled an invaluable geological criterion for gold targeting with a considerable level of certainty.

Innovative use of spatial regression models to predict the effects of green infrastructure on land surface temperatures

Understanding the complex and dynamic interplay and cumulative effects of green infrastructure (GI) and urban form on land surface temperatures (LST) is important to design and implement heat mitigation strategies. Past research has mostly employed two-dimensional (2D) indicators, simple correlations and conventional regression models using coarse-level analytical approaches that obviate spatial autocorrelation effects. For the first time, this study applies a holistic approach to evaluate GI and urban settings as complex dynamic systems. The objectives of this paper are to: (1) develop novel ‘spatially-based’ predictive models that account for spatial dependencies; (2) implement a fine-scale analytical unit (<50 m) for a more precise and accurate analysis; (3) incorporate the ‘multi-temporal’ diurnal and seasonal variations into predictions; and (4) propose the novel combination of 2D and 3D morphological, compositional and configurational parameters of GI and urban form derived from very high resolution (VHR) remotely-sensed data (<2m), using Sydney metropolitan region as case study. Results show a strong spatial association of LST at fine scale (<50 m) and spatial autocorrelation among residuals in traditional models. Spatial error model (SEM) exhibits a superior performance over conventional multivariate regression, however, results presented significant heteroscedasticity caused by the large temperature variability in certain areas, although this problem was partially solved. Future studies should incorporate unmeasured factors related to material-specific properties (i.e. albedo, emissivity), and capture the thermal variation within urban areas by segmenting datasets into zones with relatively homogenous thermal and physical properties. Overall, ground imperviousness mostly defines the LST profile of a place, with a relative warming effect of 0.23 °C and 0.61 °C during day; and 0.18 °C and 0.41 °C at night per 10% of area increment in winter and summer, respectively. The same increment in the proportion of water and trees contributes to a maximum LST reduction of 0.42–0.85 °C in summer, and 0.25–1.17 °C in winter; however, this causes an increase of nocturnal LST between 0.12 °C and 0.30 °C throughout the year. In general, the cooling effects from GI do not outweigh the warming effects from man-made surfaces. Compared to abundance, the spatial configuration of trees is less influential on LST. Ground sky view factor (GSVF), altitude and distance to coast are of relative importance in defining LST profiles. These results used to numerically simulate different greening scenarios at neighbourhood scale for Sydney; illustrating the potential of spatial models to define heat mitigation scenarios to inform urban design and planning policies.

People or Places that Don’t Matter? Individual and Contextual Determinants of the Geography of Discontent

abstract The rise of a geography of political discontent in the EU documented in recent studies highlights a strong spatial association between antisystem voting, regional economic decline, and poor occupational opportunities, suggesting that economic disparities within the EU are the origin of some of the most recent and shocking political events like Brexit. This article reexamines this statement by disentangling the effect on individual and political discontent of different socioeconomic disadvantage conditions at the interregional, intraregional, and individual level. Making use of a large data set on the individual and political discontent perceived by EU citizens between 2013 and 2018, our analysis confirms that a geography of discontent exists across EU regions. Nevertheless, our findings also highlight that intraregional inequalities do matter for individual discontent, and individual socioeconomic disadvantage conditions amplify further this negative effect.

A recurrent curve matching classification method integrating within-object spectral variability and between-object spatial association

Object-based image analysis (OBIA), which has been commonly used for land cover and land use classification, may encounter challenges when satellite images’ spatial resolution achieves at the sub-meter level. An image object may exhibit spectral heterogeneity, causing traditional object-level statistical measures such as mean values of the pixels in an object not suited to represent the feature of the object. Additionally, an image object may have strong spatial association with its surroundings. Traditional OBIA only considers spatial features of individual object, but ignoring spatial arrangement or spatial association between objects. This paper proposes a new OBIA method by integrating within-object spectral variability and between-object spatial association. The within-object spectral variability is captured by the histograms of the pixels in an object across multispectral bands to reflect the heterogeneity of their pixel values. Based on this, the initial classification result is obtained using non-parametric curve matching methods. Then, the between-object spatial association is represented by curves derived from the frequency of pairwise classes in four main directions, also in the form of curves. The curves now composed of both the histograms of spectral feature and the class pair frequency of spatial feature are then fused for another curve matching based classification. This recurrent process is repeated and the spatial association is recaptured from the previous classification result at each iteration until a stopping criterion is satisfied. The curve matching classification method based on histograms of spectral feature is superior to traditional OBIA based on only object-level statistical measures since it fully characterizes spectral variability in the objects. The between-object spatial association works as a spatial filter that considers spatial arrangement of classes in a neighborhood. The developed method is especially suitable for classifying high spatial resolution (HSR) images with land cover/land use classes in typical urban areas.

Mercapturate pathway metabolites of sotorasib, a covalent inhibitor of KRASG12C, are associated with renal toxicity in the Sprague Dawley rat

Sotorasib is a first-in class KRASG12C covalent inhibitor in clinical development for the treatment of tumors with the KRAS p.G12C mutation. In the nonclinical toxicology studies of sotorasib, the kidney was identified as a target organ of toxicity in the rat but not the dog. Renal toxicity was characterized by degeneration and necrosis of the proximal tubular epithelium localized to the outer stripe of the outer medulla (OSOM), which suggested that renal metabolism was involved. Here, we describe an in vivo mechanistic rat study designed to investigate the time course of the renal toxicity and sotorasib metabolites. Renal toxicity was dose- and time-dependent, restricted to the OSOM, and the morphologic features progressed from vacuolation and necrosis to regeneration of tubular epithelium. The renal toxicity correlated with increases in renal biomarkers of tubular injury. Using mass spectrometry and matrix-assisted laser desorption/ionization, a strong temporal and spatial association between renal toxicity and mercapturate pathway metabolites was observed. The rat is reported to be particularly susceptible to the formation of nephrotoxic metabolites via this pathway. Taken together, the data presented here and the literature support the hypothesis that sotorasib-related renal toxicity is mediated by a toxic metabolite derived from the mercapturate and β-lyase pathway. Our understanding of the etiology of the rat specific renal toxicity informs the translational risk assessment for patients.

Geochemistry of the upper estuarine sediments of the Santos estuary: provenance and anthropogenic pollution

Major and trace element geochemistry of the upper estuarine sediments of the Santos estuary has been used to characterize sediment geochemistry, classification, distribution, and possible sources of industrial pollution. The vertical sediment cores were collected on the margin of the Cubatão, Perequê, Mogi, Piaçaguera and Jurubatuba rivers, the main effluents of the Santos estuarine system. Samples of selected basement rocks (n=12), industrial waste (n=2) and one weathering profile (organic soil, residual soil and saprolite rock) were also analyzed. The sedimentary deposits showed interbedding of medium, fine, and very fine sands in the upper portion of the estuary and subordinate silt-clay units derived from lower energy in swamp/mangroves deposits in the lower estuary. Marked geochemical differences occurred among these fluvial sediments. The calculated indices of chemical weathering, such as Chemical Index of Alteration (CIA) and A-CN-K ternary diagram indicate that the estuarine sediments display a wide range of weathering effects, from unweathered derived of Proterozoic gneiss and granitic rocks to intensely weathered site in the swamp deposits of the Piaçaguera River. Phosphogypsum waste stored in the catchment area of the Mogi River showed high concentrations of S, La, Ce, Ca, Sr, Nd, Nb, U, Ba, P, Y and F when compared with the regional rocks, soils and fluvial sediments samples analyzed in the study area, which make it a potential source of environmental contamination. The UCC-normalized patterns, geoaccumulation indexes (Igeo), robust linear regression (RA) and principal component analysis (PCA) were used to identify geochemical anomalies and discuss their probable sources. The principal component scores exhibited strong spatial association with anthropogenic sources. The principal component loading allowed to separate heavy metal elements (Cr, Cu, Ni, Pb and Zn) from the elements related to phosphogypsum waste (e.g., Ce, La, Nd and F). The geochemical anomalies of Ce, La, Nd and F in the fluvial sediments of the Mogi downstream River may be related to phosphogypsum waste in the catchment area, whereas the Cr, Cu and Ni anomalies may be related to fossil fuel, chemical industries and industrial waste deposits which occur near the Pereque and Cubatão rivers.