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Effects of organic fertilizer replacement on the microbial community structure in the rhizosphere soil of soybeans in albic soil
A long-read sequencing approach to high-resolution profiling of bacterioplankton diversity in a shallow freshwater lake
Mechanical properties of alkali activated geopolymer cement mortar for non vibratory compacted trench backfilling
Polyurethane-based foam composites: synthesis, structural characteristics, and radiation shielding properties
Abstract This study investigates the potential of pure polyurethane (PU) foam as a lightweight, cost-effective shielding material against ionizing radiation, emphasizing its adaptability for incorporating high-performance fillers. PU foam was doped with various materials, including NiO, ZnO, Cr2O3, MnO2, BaO(Fe2O3)6, and sludge (at 44.5 wt.% loading), to enhance its shielding properties. The synthesized composites were characterized using Fourier Transform Infrared Spectroscopy (FT-IR), Scanning Electron Microscopy (SEM), and X-ray Fluorescence (XRF). Radiation shielding performance was evaluated through Monte Carlo simulations (MCNP) and Phy-X software for γ-rays (0.015–15 MeV) and fast neutron attenuation (up to 11 MeV). Results showed that incorporating high-density, high-atomic-number fillers significantly improved γ-ray attenuation, with BaO(Fe2O3)6 demonstrating the highest linear attenuation coefficient. Conversely, pure PU foam effectively attenuated fast neutrons due to its high concentration of light elements. The findings highlight PU-based composites as promising materials for γ-ray and neutron shielding, particularly in X-ray protection and radiological safety applications.
Development of an iridium complex fluorescent probe for FGF21 protein labeling and tracking
Deconstruction of rubber via C–H amination and aza-Cope rearrangement
Anti-windup control of saturated switched delayed systems with actuator faults
Enhancing autonomous exploration for robotics via real time map optimization and improved frontier costs
Abstract Autonomous exploration and mapping in unknown environments remain pivotal in robotics research. The efficiency of autonomous exploration is often constrained by irrational exploration strategies and incomplete map exploration. This paper proposes an efficient autonomous exploration method based on a frontier strategy, aiming to enhance the performance of ground mobile robots in exploration and mapping tasks. We employ a real-time grid map optimization technique using bilateral filtering and expansion to eliminate inefficient frontiers, improve mapping quality, and enhance the overall efficiency of autonomous exploration. Additionally, we construct a novel frontier cost function that incorporates factors such as path length, sensor measurement range, and information gain. Our approach uniquely combines an autonomous exploration decision model with the Minimum Ratio Travelling Salesman Problem (MRTSP) to maximize the explored area within the shortest possible path. Comparative analyses with classic methods, conducted in both simulated and real environments, demonstrate a 10–30% improvement in exploration efficiency through our approach.
Dose-dependent dual effects of HDAC inhibitors on glial inflammatory response
Abstract Neuroinflammation is defined as a process that includes cellular responses designed to protect the central nervous system from external influences, and it initiates in cases of extreme deviations from homeostasis. While it serves a protective role, excessive immune activation can lead to the release of neurotoxic factors, worsening disease progression. Histone deacetylases (HDACs) have been shown to modulate the expression of inflammatory genes by remodeling chromatin through the process of histone deacetylation. HDAC inhibitors (HDACi) alter histone acetylation and affect the transcription of genes involved in inflammatory pathways, making them promising therapeutic tools for the modulation of a variety of inflammatory diseases. However, their use is limited due to non-specific targeting and contradictory results. This study aimed to reconcile conflicting results and share insights on relevant HDACi in the inflammatory response induced by lipopolysaccharide (LPS), considering different exposure scenarios, cellular models, and associated molecular pathways. Specifically, the study evaluated the dose-dependent effects of two broad-spectrum HDACi, Trichostatin A (TSA) and Suberoylanilide Hydroxamic Acid (SAHA, Vorinostat), alongside selective inhibitors—MS-275 (Entinostat, class I), and MC1568 (class II)—on the expression and release of pro- and anti-inflammatory cytokines. Broad-spectrum HDAC inhibitors TSA and SAHA exhibited dose-dependent modulation of LPS-induced cytokine release. Co-treatment with TSA and LPS enhanced pro-inflammatory cytokines (TNF-α, IL-1β) and decreased IL10 in a dose-dependent manner at lower doses (≤ 10 nM), while high concentrations (100 nM) induced the anti-inflammatory IL-10. Pre-treatment with TSA led to a reduction in TNF-α levels induced by LPS, without affecting IL-1β or IL-10 levels. In contrast, the presence of TSA in LPS-triggered alveolar macrophages resulted in a decline in the production of both pro- and anti-inflammatory cytokine, irrespective of the TSA concentration. SAHA exhibited dual effects, enhancing TNF-α and IL-1β at nanomolar levels but suppressing TNF-α at micromolar doses in co-treated glial cells with LPS. Class-selective inhibitors highlighted distinct HDAC roles on LPS modulation: MS-275 reduced, while MC1568 enhanced, TNF-α release, alongside varied IL-1β and IL-10 modulation. To better understand the dual effects of SAHA, transcriptomic analysis of glial cells was conducted in the presence of LPS and low and high SAHA concentrations (100 nM or 5 µM). This analysis revealed a dose-dependent alteration in gene expression and pathway enrichment associated with cytokine signaling and immune regulation (e.g., JAK-STAT). Altogether, these findings reveal insights on the subtle, dose- and context-dependent role of HDACi in modulating glia inflammation.
Certified randomness using a trapped-ion quantum processor
Abstract Although quantum computers can perform a wide range of practically important tasks beyond the abilities of classical computers1,2, realizing this potential remains a challenge. An example is to use an untrusted remote device to generate random bits that can be certified to contain a certain amount of entropy3. Certified randomness has many applications but is impossible to achieve solely by classical computation. Here we demonstrate the generation of certifiably random bits using the 56-qubit Quantinuum H2-1 trapped-ion quantum computer accessed over the Internet. Our protocol leverages the classical hardness of recent random circuit sampling demonstrations4,5: a client generates quantum ‘challenge’ circuits using a small randomness seed, sends them to an untrusted quantum server to execute and verifies the results of the server. We analyse the security of our protocol against a restricted class of realistic near-term adversaries. Using classical verification with measured combined sustained performance of 1.1 × 1018 floating-point operations per second across multiple supercomputers, we certify 71,313 bits of entropy under this restricted adversary and additional assumptions. Our results demonstrate a step towards the practical applicability of present-day quantum computers.
Deformation, failure, and crack propagation characteristics of fissured red sandstone under uniaxial compression condition
Spatiotemporal influence analysis model for cultural landscapes based on a virtual geographic environment
Hyaluronic acid modified chuanxiong oil liposomes as a novel therapeutic agent for photoaging prevention
Analysing factors underlying the reporting of established non-native species
Abstract A nexus of natural and human variables mediate the success of non-native species that threaten global biodiversity and ecological stability. However, the relative importance and interplays among relevant factors has not been holistically approached. To identify spatial differences and potential connections in relevant natural and human drivers, we analyzed the number of non-native species established in European countries using a newly collated database of established non-native species. We employ a series of broadscale national predictors classified into ‘research’, ‘economy’, ‘environment & culture’, and ‘land-use’ to predict successful establishment. Our null models, which assume the distribution of non-native species mirrors that of each predictor, accurately predicted non-native species numbers across European countries. However, a few countries were identified as outliers, having significantly over- or underrepresented non-native species numbers based on adjusted quasi-Poisson distribution quantiles. A network analysis of non-native species compositions identified these regions to be central hubs (e.g. Germany, France, and Switzerland), but also highlighted distinct spatial similarities across European countries. Combinations of the predictors ‘economy’, ‘research’, and ‘environment & culture’ explained the largest shares of differences in the number of established non-native species among European countries as well as their reporting rates over time. Individual drivers alone were insufficient to wholly explain national differences, whereas interacting driver categories ultimately accounted for the largest shares of variance. This analysis demonstrates the breadth of predictors that mediate successful establishment, and particularly highlights the relevance of overlooked historical-cultural facets affecting biological invasions.
Temporal dynamics and relationship between negative air ions and environmental factors in subtropical forests, China
A small-molecule SARS-CoV-2 inhibitor targeting the membrane protein
Abstract The membrane (M) protein of betacoronaviruses is well conserved and has a key role in viral assembly 1,2 . Here we describe the identification of JNJ-9676, a small-molecule inhibitor targeting the coronavirus M protein. JNJ-9676 demonstrates in vitro nanomolar antiviral activity against SARS-CoV-2, SARS-CoV and sarbecovirus strains from bat and pangolin zoonotic origin. Using cryogenic electron microscopy (cryo-EM), we determined a binding pocket of JNJ-9676 formed by the transmembrane domains of the M protein dimer. Compound binding stabilized the M protein dimer in an altered conformational state between its long and short forms, preventing the release of infectious virus. In a pre-exposure Syrian golden hamster model, JNJ-9676 (25 mg per kg twice per day) showed excellent efficacy, illustrated by a significant reduction in viral load and infectious virus in the lung by 3.5 and 4 log 10 -transformed RNA copies and 50% tissue culture infective dose (TCID 50 ) per mg lung, respectively. Histopathology scores at this dose were reduced to the baseline. In a post-exposure hamster model, JNJ-9676 was efficacious at 75 mg per kg twice per day even when added at 48 h after infection, when peak viral loads were observed. The M protein is an attractive antiviral target to block coronavirus replication, and JNJ-9676 represents an interesting chemical series towards identifying clinical candidates addressing the current and future coronavirus pandemics.
Techno-economic and environmental analysis of a fully renewable hybrid energy system for sustainable power infrastructure advancement
Spatiotemporal evolution and multiscenario simulation of cultivated land ecosystem services in the Dongting Lake Plain
Vulnerability of Gubernatrix cristata to climate change, anthropogenic pressures, and hybridization threats
Abstract Estimating extinction risk is challenging due to insufficient data on current and future threats. This study develops a framework incorporating the impacts of climate change, anthropogenic pressures, and biotic interactions for assessing extinction risks using the endangered Yellow Cardinal (Gubernatrix cristata) as a case study. Using ecological niche modeling (ENM) with occurrences, climate, and land use data, we projected current and future distributions of G. cristata, identifying key constraints for its occurrence. Field validation through a citizen science initiative contributed new presence records, supporting our model’s predictions. Currently, 4.50% of cardinal’s suitable areas overlap with areas of high anthropic pressures, while 27.04% are in contact with the hybridizing species Diuca diuca. Future projections predict a 60% shift in the cardinal’s distribution, exacerbating its vulnerability due to greater overlap with areas of high anthropic pressures and reduced presence in protected areas. We identified key risk areas on the distribution’s periphery, vulnerable to geographic range loss and increased interaction with D. diuca due to climate change. Targeted management actions are recommended to mitigate further degradation. This study illustrates the potential of integrating citizen science, ENM, and anthropogenic and biotic pressures to develop conservation strategies, offering a versatile, universally applicable framework crucial for global biodiversity and conservation efforts.