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A tridimensional framework for governance in the wildland-urban interface using Pyro-Socio-Ecological Zones
Abstract Zones where urban land covers meet wildland areas have become a critical point of interaction between human settlements and natural ecosystems at risk of wildfire. These zones span diverse socioeconomic, governance, and ecological dimensions that are often not accounted for with frequently used methodologies. We developed and mapped a tri-dimensional Pyro-Socio-Ecological Zone (PSEZ) framework based on a suite of composite indicators that account for disparate Ecological, Socioeconomic, and Governance contexts in southern Italy (IT) and southern California (CA), USA. In CA, PSEZ with high governance consistently present a lower number of wildfires compared to PSEZ with low governance values. In IT, PSEZ with low governance indicate a lower number of wildfires and more burned area while PSEZ with high governance levels had more wildfires and less burned area. Overall, we found that the distribution of PSEZs and wildfire governance implications differed between CA and IT, underscoring greater spatial fragmentation, disparate contexts, and complex socio-ecological interactions in these peri-urban areas. Findings highlight that care is warranted when applying USA derived methods and concepts to fire-prone, landscapes in different geographies and contexts.
Correction: Comparison of Simoa, high‑sensitivity ELISA, and CLIA for serum neurofilament light chain quantification in multiple sclerosis
Mystery owner of African hominin foot identified
Defect Engineering for Stabilizing Magnetic and Topological Properties in Mn(Bi1-xSbx)2Te4
Folic acid inhibits the Wnt/β-catenin pathway by upregulating DKK3 to exert anti-tumor effects in cervical squamous cell carcinoma
Lack of caspase 8 directs neuronal progenitor-like reprogramming and small cell lung cancer progression
Abstract Most neuroendocrine cancers lack caspase 8 protein expression. While this feature was thought to facilitate escape from extrinsic apoptosis, its cancer-regulatory function has remained unexplored. Here, we devise a mouse model of small cell lung cancer (SCLC) recapitulating the lack of expression of caspase 8 seen in humans and uncover an unexpected role for necroptosis-fueled pre-tumoral inflammation resulting in reprogramming towards a neuronal progenitor cell-like state and increased metastatic disease. Notably, transcriptional signatures of this cellular state are enriched in relapsed and metastatic human SCLC. Mechanistically, caspase 8 loss within the pre-tumoral niche promotes inflammation marked by increased recruitment of regulatory T cells (Tregs) which are responsible for the promotion of metastatic disease. Importantly, inactivation of the necroptosis executioner MLKL reverses pre-tumoral inflammation, decreases metastasis as well as neuronal-like reprogramming. Taken together, our findings suggest that pre-tumoral inflammatory cell death contributes to neuronal progenitor mimicry, immunosuppression and increased metastasis in SCLC.
Highest early blood pressure within 24 hours and mortality after in-hospital cardiac arrest in the oldest ICU patients: A binational cohort study
Stereotactic body radiotherapy with sintilimab and bevacizumab biosimilar in anti-PD-1 refractory hepatocellular carcinoma: the ReUNION-1 phase 2 trial
A dual-branch multi-modal deep learning framework for non-destructive evaluation of intramuscular fat in sheep
Abstract The content of Intramuscular Fat (IMF) is a critical determinant of sheep quality, directly influencing its flavor, tenderness, and juiciness. Although deep learning offers a promising avenue for non-destructive prediction, research has predominantly centered on pork, leaving sheep quality assessment underexplored and highlighting a critical scarcity of public, large-scale multimodal datasets. To overcome the insufficient representational power of single-modality approaches (e.g., B-mode ultrasound images), this paper makes two primary contributions. First, we construct and release a comprehensive multimodal sheep dataset, containing 1,728 samples of ultrasound images, corresponding attributes, and ground-truth IMF values. Second, we propose DB-KAN, a novel dual-branch regression network designed to leverage this rich data. DB-KAN features a Convolutional Neural Network (CNN) branch to extract spatial features from ultrasound images and a Transformer branch to process structured attributes like backfat thickness, eye muscle depth, and eye muscle area measured at the 12th/13th rib site. This dual-branch architecture effectively captures heterogeneous information. Crucially, the decoder innovatively incorporates a KAN-Based regression head (KBRH), which efficiently fuses these multimodal features for a precise final prediction. Experiments on our dataset, partitioned 8:1:1 for training, validation, and testing, demonstrate that DB-KAN achieves state-of-the-art performance. Ablation studies further validate the indispensable roles of both the dual-branch design and the KAN-based fusion strategy.
Minor SHIV variants abrogate protective efficacy of broadly neutralizing antibodies in rhesus macaques
Zwitterionic nanocomposites grafted onto titanium dioxide enhanced water-based drilling fluid for high-temperature and high-salinity deep resource development
X-ray-diffraction and electrical-transport imaging of superconducting superhydride (La,Y)H10
Abstract Understanding how microscopic structural domains govern macroscopic electronic properties is central to advancing hydride superconductors, yet such correlations remain poorly resolved under pressure. We report the synthesis and characterization of (La 0.9 Y 0.1 )H 10 superhydrides exhibiting coexisting cubic $${Fm}\bar{3}m$$ F m 3 ¯ m and hexagonal $$P{6}_{3}/{mmc}$$ P 6 3 / m m c clathrate phases observed over the pressure range from 168 GPa down to 136 GPa. Using synchrotron-based X-ray diffraction imaging at the upgraded Advanced Photon Source, we spatially resolved μm-scale distributions of these phases, revealing structural inhomogeneity across the sample. Four-probe resistance measurements confirmed superconductivity with two distinct transitions: an onset at 244 K associated with the cubic phase and a second near 220 K linked to the hexagonal phase. Notably, resistance profiles collected from multiple current and voltage permutations showed variations in transition width and onset temperature that correlated with the spatial phase distribution. These findings demonstrate a direct connection between local structural domains and superconducting behavior.
Characterization of ficus hispida fruit extract and assessment of Gallic acid using in Silico and in vitro studies against breast cancer
Author Correction: Exploring the space of self-reproducing ribozymes using generative models
Multi-temporal dimension prediction of new energy electricity demand based on chaos-LSSVM neural network
Ancient DNA offers clues about mysterious prehistoric settlement in China
Thermal dynamics and coalescence of Au144(SR)60 clusters from a machine-learned potential
Abstract Ligand-protected metal nanoclusters have gained significant attention due to their diverse applications in catalysis, bioimaging, and nanomedicine. While their ground-state electronic structure and optical properties have been extensively studied via density functional theory (DFT) methods, theoretical insights into their dynamic behavior, particularly for larger clusters, remain scarce due to the prohibitive numerical cost of long-timescale simulations using forces calculated from DFT. Here we investigate, using molecular dynamics (MD) simulations up to 0.12 μs timescale, thermal dynamics of the well-known Au 144 (SR) 60 at 300-550 K using the recently parametrized atomic cluster expansion (ACE) potential, trained from DFT data for thiolate-protected gold clusters. Our findings reveal that thermal effects induce increased mobility in a layer-by-layer fashion, leading to formation of polymeric gold-thiolate units and rings which may fragment from the cluster at high temperatures. The remaining smaller clusters resemble experimentally observed cluster compositions. Close interaction of two Au 144 (SR) 60 clusters leads to coalescence, resulting in a cluster composition and structure of the inner metal core close to ones identified in previous experiments. This work reveals mechanisms for thermal effects in ligand-protected gold clusters and larger nanoparticles that are instrumental for understanding their catalytic activity and inter-particle reactions at the atomistic level.