Spatial variation in genomic signatures of local adaptation during the cane toad invasion of Australia.

Adaptive evolution can facilitate species' range expansions across environmentally heterogeneous landscapes. However, serial founder effects can limit the efficacy of selection, and the evolution of increased dispersal during range expansions may result in gene flow swamping local adaptation. Here, we study how genetic drift, gene flow and selection interact during the cane toad's (Rhinella marina) invasion across the heterogeneous landscape of Australia. Following its introduction in 1935, the cane toad colonised eastern Australia and established several stable range edges. The ongoing, more rapid range expansion in north-central Australia has occurred concomitant with an evolved increase in dispersal capacity. Using reduced representation genomic data of Australian cane toads from the expansion front and from two areas of their established range, we test the hypothesis that high gene flow constrains local adaptation at the expansion front relative to established areas. Genetic analyses indicate the three study areas are genetically distinct but show similar levels of allelic richness, heterozygosity and inbreeding. Markedly higher gene flow or recency of colonisation at the expansion front have likely hindered local adaptation at the time of sampling, as indicated by reduced slopes of genetic-environment associations (GEAs) estimated using a novel application of geographically weighted regression that accounts for allele surfing; GEA slopes are significantly steeper in established parts of the range. Our work bolsters evidence supporting adaptation of invasive species post-introduction and adds novel evidence for differing strengths of evolutionary forces among geographic areas with different invasion histories.

A novel artificial intelligence network to assess the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features.

Background: Immune checkpoint inhibitors (ICIs) have revolutionized gastrointestinal cancer treatment, yet the absence of reliable biomarkers hampers precise patient response prediction. Methods: We developed and validated a genomic mutation signature (GMS) employing a novel artificial intelligence network to forecast the prognosis of gastrointestinal cancer patients undergoing ICIs therapy. Subsequently, we explored the underlying immune landscapes across different subtypes using multiomics data. Finally, UMI-77 was pinpointed through the analysis of drug sensitization data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The sensitivity of UMI-77 to the AGS and MKN45 cell lines was evaluated using the cell counting kit-8 (CCK8) assay and the plate clone formation assay. Results: Using the artificial intelligence network, we developed the GMS that independently predicts the prognosis of gastrointestinal cancer patients. The GMS demonstrated consistent performance across three public cohorts and exhibited high sensitivity and specificity for 6, 12, and 24-month overall survival (OS) in receiver operating characteristic (ROC) curve analysis. It outperformed conventional clinical and molecular features. Low-risk samples showed a higher presence of cytolytic immune cells and enhanced immunogenic potential compared to high-risk samples. Additionally, we identified the small molecule compound UMI-77. The half-maximal inhibitory concentration (IC50) of UMI-77 was inversely related to the GMS. Notably, the AGS cell line, classified as high-risk, displayed greater sensitivity to UMI-77, whereas the MKN45 cell line, classified as low-risk, showed less sensitivity. Conclusion: The GMS developed here can reliably predict survival benefit for gastrointestinal cancer patients on ICIs therapy.

Scaling relationships between the total number of leaves and the total leaf area per culm of two dwarf bamboo species.

Total leaf area per plant is an important measure of the photosynthetic capacity of an individual plant that together with plant density drives the canopy leaf area index, that is, the total leaf area per unit ground area. Because the total number of leaves per plant (or per shoot) varies among conspecifics and among mixed species communities, this variation can affect the total leaf area per plant and per canopy but has been little studied. Previous studies have shown a strong linear relationship between the total leaf area per plant (or per shoot) (A T) and the total number of leaves per plant (or per shoot) (N T) on a log-log scale for several growth forms. However, little is known whether such a scaling relationship also holds true for bamboos, which are a group of Poaceae plants with great ecological and economic importance in tropical, subtropical, and warm temperate regions. To test whether the scaling relationship holds true in bamboos, two dwarf bamboo species (Shibataea chinensis Nakai and Sasaella kongosanensis 'Aureostriatus') with a limited but large number of leaves per culm were examined. For the two species, the leaves from 480 and 500 culms, respectively, were sampled and A T was calculated by summing the areas of individual leaves per culm. Linear regression and correlation analyses reconfirmed that there was a significant log-log linear relationship between A T and N T for each species. For S. chinensis, the exponent of the A T versus N T scaling relationship was greater than unity, whereas that of S. kongosanensis 'Aureostriatus' was smaller than unity. The coefficient of variation in individual leaf area increased with increasing N T for each species. The data reconfirm that there is a strong positive power-law relationship between A T and N T for each of the two species, which may reflect adaptations of plants in response to intra- and inter-specific competition for light.

Forest genomics in the Caucasus through the lens of its dominant tree species - Fagus orientalis.

The last glacial period is known to have greatly influenced the demographic history of temperate forest trees, with important range contractions and post-glacial expansions that led to the formation of multiple genetic lineages and secondary contact zones in the Northern Hemisphere. These dynamics have been extensively studied for European and North American species but are still poorly understood in other temperate regions of rich biodiversity such as the Caucasus. Our study helps filling that gap by deciphering the genomic landscapes of F. orientalis across the South Caucasus. The use of genome-wide data confirmed a past demographic history strongly influenced by the Last Glacial Maximum, revealing two disjunct glacial refugia in the Colchis and Hyrcanian regions. The resulting patterns of genetic diversity, load and differentiation are not always concordant across the region, with genetic load pinpointing the location of the glacial refugia more efficiently than genetic diversity alone. The Hyrcanian forests show depleted genetic diversity and substantial isolation, even if long-distance gene flow is still present with the main centre of diversity in the Greater Caucasus. Finally, we characterize a strong heterogeneity of genetic diversity and differentiation along the species chromosomes, with noticeably a first chromosome showing low diversity and weak differentiation.

[Spatial and Temporal Scale Effects of Landscape Pattern on Riverine Nitrogen and Phosphorus Nutrients in the Qingshan Lake Watershed].

The influences of landscape pattern on water quality are dependent on spatial-temporal scales. However, the effects of landscape composition, landscape configuration, and landscape slope metrics on seasonal water quality at different spatial scales remain unclear. Based on the total nitrogen, total phosphorus, nitrate-N, and ammonium-N data from 26 sampling sites in the Qingshan Lake watershed, this study coupled landscape pattern analysis, redundancy analysis, and partial redundancy analysis to quantify the spatiotemporal scale effects of landscape pattern on riverine nitrogen （N） and phosphorus （P） concentrations. The results showed that： ① The explanatory ability of landscape pattern at the sub-watershed scale on riverine N and P concentrations was 6.8%-8.4% higher than that at the buffer scale, and this effect was more obvious in the dry season. ② At the sub-watershed scale, the percentage of forestland and the interspersion and juxtaposition degree of residential land had a greater influence on riverine N and P concentrations. At the buffer scale, the slope of farmland and residential land and the aggregation degree of forestland patches were the key factors affecting riverine N and P concentrations. ③ The contribution rate of landscape configuration to riverine N and P concentration variations （20.1%-36.5%） was the highest. The sensitivity of the effect of landscape configuration on riverine N and P concentrations to seasonal changes was the highest, and the effect of landscape slope on riverine N and P concentrations had the highest sensitivity to spatial scale changes. Therefore, landscape pattern-regulated non-point source pollution should be considered from a multi-scale perspective. These results can provide scientific basis for the formulation of landscape pattern optimization measures aiming at non-point source pollution control.

Land use and spatial contiguity are key driven factors of antibiotic multimedia patterns in the megacity river network.

The widespread spread of antibiotics in the environment poses a growing threat to human health. This study investigated the distribution and fate of antibiotics concerning land use characteristics, hydrological conditions, and spatial contiguity within a megacity river network. Temporally, the average concentrations of twenty antibiotics in water (354 ng/L), suspended particulate matter (SPM) (46 ng/L), and sediment (151 ng/g) during dry season were notably higher than that in the corresponding environment media (water: 127 ng/L, SPM: 2 ng/L, and sediment: 49 ng/g) during the wet season. Moreover, the inter-annual variation of antibiotics in water showed a decreasing trend. Spatially, substantial antibiotic contamination was observed in a human-intensive watershed, particularly in the upstream and central city sections. The macrolides in water were most affected by land use types and hydrological processes. Antibiotic contamination in water exhibited a stronger spatial autocorrelation compared to other media. Nevertheless, the interconnectedness of antibiotic contamination in sediments during the wet season warrants attention, and relevant authorities should enhance environmental monitoring in watersheds with pollution hotspots. Certain antibiotics, such as sulfamethoxazole, enrofloxacin, and florfenicol, were transported via urban rivers to the ocean, potentially posing environmental risks to coastal water quality. Local sources accounted for the predominant portion (>50 %) of most antibiotics in various media. The correlation distances of antibiotics in waters during the wet season could screen ecological risk prioritization in aquatic environments.

Impact of seasonal changes in urban green spaces with diverse vegetation structures on college students' physical and mental health.

Based on the perceptions of college student participants in winter and summer, the effects of different vegetation structures within landscapes (single-layer woodland, tree-shrub-grass composite woodlands, tree-grass composite woodland, and single-layer grassland) and concrete squares without plants were investigated, and the skin conductivity level (SCL) and environmental perception recovery score (PRS) associated with landscape types were calculated. The results indicated that seasonal differences in landscape perception significantly affected college student participants' PRS but not their SCL scores, both in winter and summer. Viewing single-layer and tree-shrub-grass composite woodlands in summer, as well as single-layer woodland in winter, enhanced the environmental perception of the college student participants. The restorative effects of the four vegetation types in green spaces were ranked as follows: single-layer woodland, tree-shrub-grass composite woodlands, single-layer grassland, and tree-grass composite woodlands and concrete squares without plants. These findings underscore the importance of considering seasonal variations when choosing plant species for landscaping purposes, with evergreen single-layer woodland being a suitable choice for winter urban landscapes. This provides a scientific basis for assessing landscape perception and preferences in the future.

Spatiotemporal dynamic relationships and simulation of urban spatial form changes and land surface temperature: a case study in Chengdu, China.

Exploring the spatiotemporal dynamic evolution of local climate zones (LCZ) associated with changes in land surface temperature (LST) can help urban planners deeply understand urban climate. Firstly, we monitored the evolution of 3D urban spatial form in Chengdu City, Sichuan Province, China from 2010 to 2020, used the ordinary least squares model to fit the dynamic correlation (DR) between the changes in urban spatial patterns and changes in LST, and revealed the changes of urban spatial patterns closely related to the rise in LST. Secondly, the spatiotemporal patterns of LST were examined by the integration of the Space-Time Cube model and emerging hotspot analysis. Finally, a prediction model based on curve fitting and random forest was integrated to simulate the LST of study area in 2025. Results show the following: the evolution of the urban spatial form consists of three stages: initial incremental expansion, midterm incremental expansion and stock renewal, and late stock renewal and ecological transformation. The influence of the built environment on the rise of LST is greater than that of the natural environment, and the building density has a greater effect than the building height. The overall LST shows a warming trend, and the seven identified LST spatiotemporal patterns are dominated by oscillating and new hotspots patterns, accounting for 51.99 and 11.44% of the study area, respectively. The DR between urban spatial form and LST varies across different time periods and built environment types, whereas the natural environment is always positively correlated with LST. The thermal environment of the city will warm up in the future, and the area affected by the heat island will shift to the central of the city.

Predator in proximity: how does a large carnivore respond to anthropogenic pressures at fine-scales? Implications for interface area management.

Background: Driven by habitat loss and fragmentation, large carnivores are increasingly navigating human-dominated landscapes, where their activity is restricted and their behaviour altered. This movement, however, raises significant concerns and costs for people living nearby. While intricately linked, studies often isolate human and carnivore impacts, hindering effective management efforts. Hence, in this study, we brought these two into a common framework, focusing on an interface area between the critical tiger habitat and the human-dominated multiple-use buffer area of a central Indian protected area. Methods: We employed a fine-scale camera trap survey complemented by GPS-collar movement data to understand spatio-temporal activity patterns and adjustments of tigers in response to anthropogenic pressures. We used an occupancy framework to evaluate space use, Bayesian circular GLMs to model temporal activity, and home range and step length analyses to assess the movement patterns of tigers. Further, we used predation-risk models to understand conflict patterns as a function of tiger presence and other habitat variables. Results: Despite disturbance, a high proportion of the sampled area was occupied by 17 unique tigers (ψ = 0.76; CI [0.73-0.92]). The distance to villages (ß ± SE = 0.63 ± 0.21) and the relative abundance of large-bodied wild prey (ß ± SE = 0.72 ± 0.37) emerged as key predictors of tiger space use probability, indicating a preference for wild prey by tigers, while human influences constrained their habitat utilisation. Distance to villages was also identified as the most significant predictor of the tigers' temporal activity (µ ± σ = 3.03 ± 0.06 rad) that exhibited higher nocturnality near villages. A total of 11% of tiger home ranges were within village boundaries, accompanied by faster movement in these areas (displacement 40-82% higher). Livestock depredation probability by tigers increased with proximity to villages (P = 0.002) and highway (P = 0.003). Although tiger space use probability (P = 0.056) and wild prey abundance (P = 0.134) were non-significant at the 0.05 threshold, their presence in the best-fit predation-risk model suggests their contextual relevance for understanding conflict risk. The results highlight the importance of appropriately managing livestock near human infrastructures to effectively mitigate conflict. Conclusions: Shared space of carnivores and humans requires dynamic site-specific actions grounded in evidence-based decision-making. This study emphasises the importance of concurrently addressing the intricate interactions between humans and large carnivores, particularly the latter's behavioural adaptations and role in conflict dynamics. Such an integrated approach is essential to unravel cause-effect relationships and promote effective interface management in human-dominated landscapes.

Assessing the role of habitat, climate, and anthropization gradients on terrestrial mammal diversity in the western Mediterranean basin.

Mammal species globally exhibit distribution patterns conditioned by environmental conditions and human impact. The Mediterranean basin provides an ideal system to study these effects due to its diverse climate, and habitat conditions. In this work, we aim to assess the impact of landscape heterogeneity and anthropization degree on terrestrial mammal diversity in this region. Accordingly, we deployed over 300 camera traps across 28 sites for 3 months. Detected mammal species (weighing more than 1kg) were classified as domestic carnivores, domestic ungulates, wild carnivores, wild ungulates, lagomorphs, and large rodents. Alpha and beta diversity were calculated for each group and all wild mammals. Simple linear regressions and multimodal analysis were conducted between mammal diversities and climate, environmental conditions, landscape heterogeneity, and anthropization degree variables. Redundancy analyses were performed to identify variables and species determining the mammalian community composition. Indexes measuring landscape heterogeneity, anthropization degree, and its 30-year change did not correlate with mammal diversity. However, the difference in elevation within sites and domestic carnivore abundance showed a significant positive correlation with some of the diversity indexes. Nonetheless, rainfall and mean elevation factors generally showed the highest correlation with mammal diversity. Instead, a few influential species, including generalists and open-habitat specialists, highlighted the importance of conserving open areas, as well as the importance of the Pyrenees region as a key habitat for certain species. Therefore, climatic variables emerged as the key determinants of mammal diversity, highlighting climate change as a potential threat to mammal diversity in this area.

Effects of Human Harvesting, Residences, and Forage Abundance on Deer Spatial Distribution.

It has been known that harvesting by humans strongly influences individual within-home range habitat selection of many deer species; however, little is known about the effect of harvesting on coarse-scale habitat selection (i.e., spatial distribution). We examined the summer spatial distribution of sika deer Cervus nippon in relation to human harvesting and other factors, such as human residences, forage abundance, and cover, using pellet group counts at Mount Fuji, central Japan, in 2018. In the study area, harvesting is conducted at medium elevation areas throughout the year, but not at high or low elevation areas where access is difficult or harvesting is prohibited. Spatial distribution of deer was significantly biased to non-harvesting areas and far from residential areas, suggesting that they avoid riskier spaces by establishing a landscape of fear. High-quality food resources (deciduous broad-leaved trees and forbs) were more abundant in harvesting areas than in non-harvesting areas, suggesting that foraging pressure by deer reduce them. However, there were no differences in abundances of more fibrous dwarf bamboo between harvesting and non-harvesting areas, and spatial distribution of deer was significantly biased to higher dwarf bamboo abundance areas, suggesting that the dwarf bamboo is an alternative food resource in non-harvesting areas where supplies of high-quality food were limited. Our results suggest that human harvesting pressure and residences shifted the spatial distribution of deer from the montane forests to subalpine/alpine zones, which may increase damage to vulnerable ecosystems due to severe foraging pressure.

Mutations in LIFR rewire the JAK/STAT signaling pathway: A study unveiling mechanistic details of Stüve-Wiedemann syndrome.

Stüve-Wiedemann syndrome (SWS), a rare autosomal recessive disorder, characterized by diminutive size, curvature of the elongated bones, bent fingers, episodes of heightened body temperature, respiratory distress or periods of breath-holding, and challenges with feeding, especially causes fatality in infants. SWS is an outcome of potential missense mutations in the leukemia inhibitory factor receptor gene reflected as numerous amino acid mutations at protein level. Employing in silico tools and techniques like mutational screening with Pred_MutHTP, I-Mutant2.0, PANTHER.db, PolyPhen, to classify mutations as deleterious/destabilizing, in conjunction with experimental data analysis, P136A and S279P emerged as 'effect'-causing mutations. Pre-existing knowledge suggests, SWS progression is effectuated conformationally altered and dysfunctional LIFR, unable to bind to LIF and further form the LIF/LIFR/gp130 signalling complex. To gain functional insights into the effect of the said mutations on the wild type protein, an all-atom, explicit, solvent molecular dynamics simulation was performed following docking approaches. Consequently, referring to the RMSD, RMSF, protein dynamic network analysis, energy landscape plots and domain motion analysis, it was revealed that unbound LIFR_WT was more prone to LIF binding as usual whereas the mutants exhibited considerable domain closure to inhibit LIF binding. We conducted binding affinity analysis via MM/GBSA and dissociation constant estimation after LIFR-LIF docking and found the WT_complex to be more stable and compact as a whole when compared to the flexible mutant complexes thus being associated with SWS. Our study offers a route for understanding molecular level implications upon LIFR mutations which opens an avenue for therapeutic interventions.

Evolution and health risk of indicator microorganisms in landscape water replenished by reclaimed water.

As an important means to solve water shortage, reclaimed water has been widely used for landscape water supply. However, with the emergence of large-scale epidemic diseases such as SARS, avian influenza and COVID-19 in recent years, people are increasingly concerned about the public health safety of reclaimed water discharged into landscape water, especially the pathogenic microorganisms in it. In this study, the water quality and microorganisms of the Old Summer Palace, a landscape water body with reclaimed water as the only replenishment water source, were tracked through long-term dynamic monitoring. And the health risks of indicator microorganisms were analyzed using Quantitative Microbial Risk Assessment (QMRA). It was found that the concentration of indicator microorganisms Enterococcus (ENT), Escherichia coli (EC) and Fecal coliform (FC) generally showed an upward trend along the direction of water flow and increased by more than 0.6 log at the end of the flow. The concentrations of indicator microorganisms were higher in summer and autumn than those in spring. And there was a positive correlation between the concentration of indicator microorganisms and COD. Further research suggested that increased concentration of indicator microorganisms also led to increased health risks, which were more than 30% higher in other areas of the park than the water inlet area and required special attention. In addition, (water) surface operation exposure pathway had much higher health risks than other pathways and people in related occupations were advised to take precautions to reduce the risks.

Perceptible landscape patterns reveal invisible socioeconomic profiles of cities.

Urban landscape is directly perceived by residents and is a significant symbol of urbanization development. A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive, resilient, and sustainable cities and human settlements. Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing, potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes. This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators. Here, we propose four urban landscapes indicators in three dimensions (UL3D): greenness, grayness, openness, and crowding. We construct the UL3D using 4.03 million street view images from 303 major cities in China, employing a deep learning approach. We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities. The results show that UL3D indicators differs from two-dimensional landscape indicators, with a low average correlation coefficient of 0.31 between them. Urban landscapes had a changing point in 2018-2019 due to new urbanization initiatives, with grayness and crowding rates slowing, while openness increased. The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles. Specifically, GDP per capita, urban population rate, built-up area per capita, and hospital count correspond to improvements of 25.0%, 19.8%, 35.5%, and 19.2%, respectively. These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities.

Construction of ecological security pattern of arid area based on landscape ecological risk assessment: a case study of the Wu-Chang-Shi urban agglomeration.

The construction of ecological security pattern (ESP) holds paramount importance in ensuring regional environment sustainability. This study introduces an innovative approach to ESP construction grounded in landscape ecological risk (LER) assessment, with Wu-Chang-Shi urban agglomeration in Xinjiang, China, serving as a case study. Initially, LER within the area was evaluated using the LER Index (LERI) method. Subsequently, the Geodetector model was employed to discern the relationship between multi-source data and LER. Furthermore, ecological resistance and corridors were delineated utilizing the minimum cumulative resistance (MCR) model. Lastly, the corridors were optimized using the gravity model, finalizing the ESP construction. Study results reveal that LER was always fluctuating from 1990 to 2010, and tended to stabilize from 2010 to 2020. Factor detection underscores the predominant influence of land use on LER, followed by elevation and vegetation distribution. The ESP shows the imperative for improving connectivity of the natural areas that are fragmented by urban land, highlighting the great significance of the woodland-originating corridors. Finally, strategies are proposed to enhance woodland and water coverage, boost landscape diversity in nature reserves, and prioritize ecological conservation in corridor regions. In summation, the study furnishes a framework for analyzing arid regions in Eurasia. Furthermore, the research idea of evaluation-analysis-remodeling also offers insights into environmental management in developing areas with more diverse climate types.

T Cells Immune Imbalance Present in Patients With Multiple Intracranial Aneurysms.

Growing evidence suggests that systemic immune and inflammatory responses may play a critical role in the formation and development of aneurysms. Exploring the differences between single intracranial aneurysm (SIA) and multiple IAs (MIAs) could provide insights for targeted therapies. However, there is a lack of comprehensive and detailed characterization of changes in circulating immune cells in MIAs. Peripheral blood mononuclear cell (PBMC) samples from patients with SIA (n = 16) or MIAs (n = 6) were analyzed using high-dimensional mass cytometry to evaluate the frequency and phenotype of immune cell subtypes. A total of 25 cell clusters were identified, revealing that the immune signature of MIAs included cluster changes. Compared to patients with SIA, patients with MIAs exhibited immune dysfunction and regulatory imbalance in T-cell clusters. They also had reduced numbers of CD8+ T cells and their subgroups CD8+ Te and CD8+ Tem cells, as well as reduced numbers of the CD4+ T-cell subgroup CD27-CD4+ Tem cells. Furthermore, compared to SIA, MIAs were associated with enhanced T-cell immune activation, with elevated expression levels of CD3, CD25, CD27, CCR7, GP130, and interleukin 10. This study provides insights into the circulating immune cell profiles in patients with MIAs, highlighting the similarities and differences between patients with SIA and those with MIAs. Furthermore, the study suggests that circulating immune dysfunction may contribute to development of MIAs.

Exploring fine-scale urban landscapes using satellite data to predict the distribution of Aedes mosquito breeding sites.

BACKGROUND: The spread of mosquito-transmitted diseases such as dengue is a major public health issue worldwide. The Aedes aegypti mosquito, a primary vector for dengue, thrives in urban environments and breeds mainly in artificial or natural water containers. While the relationship between urban landscapes and potential breeding sites remains poorly understood, such a knowledge could help mitigate the risks associated with these diseases. This study aimed to analyze the relationships between urban landscape characteristics and potential breeding site abundance and type in cities of French Guiana (South America), and to evaluate the potential of such variables to be used in predictive models. METHODS: We use Multifactorial Analysis to explore the relationship between urban landscape characteristics derived from very high resolution satellite imagery, and potential breeding sites recorded from in-situ surveys. We then applied Random Forest models with different sets of urban variables to predict the number of potential breeding sites where entomological data are not available. RESULTS: Landscape analyses applied to satellite images showed that urban types can be clearly identified using texture indices. The Multiple Factor Analysis helped identify variables related to the distribution of potential breeding sites, such as buildings class area, landscape shape index, building number, and the first component of texture indices. Models predicting the number of potential breeding sites using the entire dataset provided an R² of 0.90, possibly influenced by overfitting, but allowing the prediction over all the study sites. Predictions of potential breeding sites varied highly depending on their type, with better results on breeding sites types commonly found in urban landscapes, such as containers of less than 200 L, large volumes and barrels. The study also outlined the limitation offered by the entomological data, whose sampling was not specifically designed for this study. Model outputs could be used as input to a mosquito dynamics model when no accurate field data are available. CONCLUSION: This study offers a first use of routinely collected data on potential breeding sites in a research study. It highlights the potential benefits of including satellite-based characterizations of the urban environment to improve vector control strategies.

Immune landscape of renal cell carcinoma with metastasis to the pancreas.

INTRODUCTION: Clear cell Renal Cell Carcinoma (ccRCC) has a poor prognosis once metastatic. However, certain metastatic sites have been reported to have a different impact on the patient prognosis. For example, patients with pancreatic metastases have a much more favorable prognosis than those with metastases to other organs. The biological basis for this observation remains poorly understood. The aim of this study was to characterize the immune landscape of pancreatic metastases and the corresponding primary tumors in order to identify possible immunological features that correlate with disease biology. PATIENTS AND METHODS: A detailed assessment of immune cell populations was performed using a total of 1,700 microscopic images from ccRCCs from 11 patients, their corresponding pancreatic metastases and ccRCCs from 10 patients without pancreatic metastases. Tumor specimens were stained for CD45, CD8, CD163 and FOXP3 and the densities of the respective immune cells were assessed semiquantitatively in the intratumoral and extratumoral compartment. Multispectral imaging was performed in selected tumors. RESULTS: We found that pancreatic metastases show the lowest intratumoral infiltration with CD8+ cytotoxic T lymphocytes of all tumor specimens analyzed. The frequency of CD8+ lymphocytes was on 1.9 fold lower in pancreatic metastases (median density 8.3 cells per field of view [FOV] = 1.23 mm2) when compared to the corresponding primary tumor (15.6 cells per FOV, P = 0.0002) and more than 3-fold lower when compared to ccRCCs without pancreatic metastases (27.2 cells per FOV, P = 0.0012). There was also a significantly reduced intratumoral infiltration with immunosuppressive FOXP3+ lymphocytes in pancreatic metastases (2.6 cells per FOV, P = 0.009) and corresponding primary tumors (2 cells per FOV, P = 0.028) when compared to ccRCCs without pancreatic metastases (5.6 cells per FOV). CONCLUSIONS: In this proof-of-concept study, we show that pancreatic metastases of ccRCC present with unique immunological features including a low intratumoral density of CD8+ and FOXP3+ lymphocytes. The low counts of CD8+ and FOXP3+ lymphocytes may reflect less aggressive features of ccRCC with pancreatic metastasis that may result in a more favorable patient prognosis.

Monitoring the developmental trend and competitive landscape of natural gas hydrate through patent analysis.

Natural gas hydrate (NGH) is a significant alternative energy resource in achieving carbon neutrality. The developmental trend and competitive landscape of NGH exploitation and production are crucial for policymakers in government, managers of enterprises, and researchers. This study introduces a novel framework for conducting an in-depth analysis of NGH, integrating patentometrics, technology evolution, and correlation relationships to monitor developmental trends and competitive landscape through patent analysis. The results indicate that China, the USA, and Japan have distinct technology advantages. Current technological developments in the NGH field focus primarily on extraction technologies, equipment, and processing systems. The co-opetition analysis among countries reveals that the most extensive international cooperation network is primarily in Europe and the USA, with national partnerships in Asia concentrated in China and Japan. Institutional cooperation remains limited, primarily within universities in China, while both the USA and Japan foster collaboration between enterprises. The competitive landscapes of key NGH-related technologies among countries and institutions are also examined. This study contributes not only to monitoring the developmental trend and competitive landscape in NGH but also to providing policy recommendations for government and enterprises regarding strategic management and collaborative innovation.

Unraveling spatial heterogeneity of soil legacy phosphorus in subtropical grasslands.

Humans have profoundly altered phosphorus (P) cycling across scales. Agriculturally driven changes (e.g., excessive P-fertilization and manure addition), in particular, have resulted in pronounced P accumulations in soils, often known as "soil legacy P." These legacy P reserves serve as persistent and long-term nonpoint sources, inducing downstream eutrophication and ecosystem services degradation. While there is considerable scientific and policy interest in legacy P, its fine-scale spatial heterogeneity, underlying drivers, and scales of variance remain unclear. Here we present an extensive field sampling (150-m interval grid) and analysis of 1438 surface soils (0-15 cm) in 2020 for two typical subtropical grassland types managed for livestock production: Intensively managed (IM) and Semi-natural (SN) pastures. We ask the following questions: (1) What is the spatial variability, and are there hotspots of soil legacy P? (2) Does soil legacy P vary primarily within pastures, among pastures, or between pasture types? (3) How does soil legacy P relate to pasture management intensity, soil and geographic characteristics? and (4) What is the relationship between soil legacy P and aboveground plant tissue P concentration? Our results showed that three measurements of soil legacy P (total P, Mehlich-1, and Mehlich-3 extractable P representing labile P pools) varied substantially across the landscape. Spatial autoregressive models revealed that soil organic matter, pH, available Fe and Al, elevation, and pasture management intensity were crucial predictors for spatial patterns of soil P, although models were more reliable for predicting total P (68.9%) than labile P. Our analysis further demonstrated that total variance in soil legacy P was greater in IM than SN pastures, and intensified pasture management rescaled spatial patterns of soil legacy P. In particular, after controlling for sample size, soil P was extremely variable at small scales, with variance diminished as spatial scale increased. Our results suggest that broad pasture- or farm-level best management practices may be limited and less efficient, especially for more IM pastures. Rather, management to curtail soil legacy P and mitigate P loading and losses should be implemented at fine scales designed to target spatially distinct P hotspots across the landscape.