Dosing requirements to untangle hormesis in plant science.

Hormesis is a trending topic in plant science, and scientific advances in this field may have a far-reaching practical impact to translate into solutions for enhancing phytohygeia under global changes. Here, I discuss strategies to optimize dosing schemes in dose-response studies and propose some fine-tuned dosing criteria in plant hormesis research.

Identification of Key Genes for Alcoholic Hepatitis Using Integrated Network Analysis of Differential lncRNA and Gene Expression.

Alcoholic liver disease (ALD) is a type of liver disease with complex pathogenic factors. In 2019, alcohol caused 11 million life-years to be lost globally, and the mortality rate has continued to rise. This study aims to explore the exclusive gene profile of AH and construct an mRNA-lncRNA regulatory network through an integrative analysis and database validation to reveal potential key biomarkers.

GSIDroid: A Suspicious Subgraph-Driven and Interpretable Android Malware Detection System.

In recent years, the growing threat of Android malware has caused significant economic losses and posed serious risks to user security and privacy. Machine learning-based detection approaches have improved the accuracy of malware identification, thereby providing more effective protection for Android users. However, graph-based detection methods rely on whole-graph computations instead of subgraph-level analyses, and they often ignore the semantic information of individual nodes.

Design and Hysteresis Compensation of Novel Resistive Angle Sensor Based on Rotary Potentiometer.

Resistive angle sensors are widely used due to their simple signal conditioning circuits and high cost-effectiveness. This paper presents a resistive angle sensor based on a rotary potentiometer, designed to offer a measurement range of 180° for low-cost angle measurement in industrial automation and electromagnetic interference (EMI)-sensitive applications. The sensor features a specially designed signal conditioning circuit and mechanical housing.

Microwave Foreign Object Detection in a Lossy Medium Using a Planar Array Antenna.

The non-contact detection of foreign objects embedded in lossy dielectric media such as soil, vegetation, or ice remains a critical challenge in applications including environmental monitoring and agricultural safety. This communication presents the design and experimental validation of an array antenna system capable of accurately localizing foreign objects in such lossy mediums. The proposed array antenna is capable of focusing electromagnetic energy at the location of the foreign object, thereby enabling precise positioning.

Pollen Quantitative and Genetic Competitiveness of Rice ( L.) and Their Effects on Gene Flow.

The gene flow rate in rice ( L.) is a critical factor for establishing safe isolation distances between genetically modified (GM) and non-GM varieties and for ensuring varietal purity in rice breeding programs. This study refines existing gene flow models by disentangling two key components of rice pollen dynamics: quantitative pollen competition and genetic competitiveness.

Electrochemical Engineering of Emerging 2D Materials beyond Graphene: Progress and Prospects.

Following the remarkable success of graphene, graphene-like 2D materials have garnered significant attention over the past decade due to their extraordinary physical and chemical properties. Despite the high demand for these materials in industry, developing facile, and cost-effective methods for large-scale production and functionalization under ambient conditions remains a challenge. As innovative green growth and modification strategies, electrochemical engineering techniques provide economic advantages in scalable manufacturing and surface manipulation.

MedKA: A knowledge graph-augmented approach to improve factuality in medical Large Language Models.

Large language models (LLMs) have demonstrated remarkable potential in medical applications. However, they still face critical challenges such as hallucinations, knowledge inconsistency, and insufficient integration of domain-specific medical expertise. To address these limitations, we introduce MedKA, a novel knowledge graph-augmented approach for fine-tuning and evaluating medical LLMs.

Quantifying anthropogenic impacts on CO₂ and CH₄ emissions: statistical insights and hotspot detection in East Africa.

East Africa (EA) faces significant challenges related to greenhouse gas (GHG) emissions, particularly carbon dioxide (CO₂) and methane (CH₄), largely driven by biomass burning (BB) from agricultural fires and wildfires. Despite their importance, the spatiotemporal variability of these emissions remains poorly understood. This study quantifies CO₂ and CH₄ emissions across EA (2001-2022), revealing significant CO₂ emission peaks in 2005 (32.

Dynamically tunable strong coupling insulator-metal phase transition in VO coupled to mid-infrared SrTiO phonons.

Dynamically tunable strong light-matter coupling in the mid-infrared (MIR) regime holds significant promise for next-generation photonic and thermal devices, especially in the long-wave infrared (LWIR) range of 19-23 μm, where vibrational and thermal signatures are most prominent. In this work, we demonstrate strong coupling between the phase-transition-tunable Fabry-Pérot (FP) cavity modes of vanadium dioxide (VO) and the phonon polaritons (PhPs) of strontium titanate (SrTiO), a polar dielectric with prominent optical phonon resonances in the LWIR region. The insulator-to-metal transition (IMT) of VO enables dynamic tuning of the coupling strength and mode hybridization.

Optimal nitrogen fertilizer rates combined with alternating wet and dry irrigation effectively reduce greenhouse gas emissions in rice-wheat rotation system under climate change scenarios.

Water and nitrogen management practices have important effects on crop yields and greenhouse gas (GHG) emissions [including methane (CH) and nitrous oxide (NO)] in rice-wheat rotation system. However, research on the effects of water and nitrogen management practices on GHG emissions and crop yields (especially CH emissions) lacks consideration of climate change. In this study, we chose the Yangtze River Delta region (YRD) as the study area, and used the Denitrification-Decomposition (DNDC) model and 25 global change models (GCMs) to simulate the effects of different water and nitrogen management practices on crop yields and GHG emissions in the rice-wheat rotation system under climate change scenarios.

How Does Climate Change Influence the Regional Ecological-Social Risks of Harmful Dinoflagellates? A Predictive Study of China's Coastal Waters.

Harmful dinoflagellates are widely distributed in coastal waters worldwide, posing multiple ecological and socioeconomic threats. Climate change may alter the biogeography of these species; however, few studies have linked shifts in harmful dinoflagellates' ecological distribution to their socioeconomic impacts. This study developed a framework to assess the spatiotemporal ecological-social risks posed by harmful dinoflagellates, identifying these algae as risk sources and considering mariculture and coastal populations as the primary risk receptors.

A one-year study of biochar in immobilizing PFOA in soil-plant rainfall leaching systems: Residue fraction and metabolomics perspectives.

The strong vertical transport capacity and facile plant uptake of perfluorooctanoic acid (PFOA) make its control in soil-plant rainfall leaching systems both urgent and challenging. This study investigated the effectiveness of biochar amendment (2 % and 4 %, w/w) in regulating the PFOA fate in a soil-lettuce system over 360 days, covering two seasons across two different soil types. Soil sequential chemical extraction and plant metabolomics analysis were employed to clarify the underlying immobilization mechanism and related metabolic outcomes.

Dual Mode Fusion Based on Rock Images and Laser-Induced Breakdown Spectroscopy to Improve the Accuracy of Discriminant Analysis.

Rocks are an extremely important and indispensable part of the Earth's crust, with wide applications in various fields such as geology, environmental monitoring, and industry. Traditional methods often rely on a single analytical technique or visual inspection, but this may not achieve the accuracy required for thorough classification. Laser-induced breakdown spectroscopy (LIBS) technology mainly provides information on the composition and content of rock elements, while images can provide appearance information such as color and texture.

Ozone pollution induced-yield loss of major staple crops in China and effects from COVID-19.

Surface ozone (O) pollution showed a continuous increasing trend during the recent decades in China, posing an increasing threat to food security. A wide range of yield reductions have been reported and thus more studies are needed to narrow down the uncertainty resulting from spatiotemporal accuracy of O metrics and extrapolation methods. Based on a high spatial resolution (0.

Influence of bulk-phase acidity, organic fraction, and dissolved oxygen on the photosensitized renoxification of nitrate in NaNO/humic acid mixtures.

Nitrate renoxification significantly influences atmospheric nitrogen cycling and global OH budgets. Although numerous nitrite acid (HONO) formation pathways from nitrate photolysis have been widely reported, the influence of various environmental factors and aerosol properties on reactive nitrogen production remains largely unclear. In this work, we employed NaNO/humic acid (HA) as a model nitrate photosensitization system to investigate the crucial roles of aerosol acidity, organic fraction, and dissolved oxygen in the production of HONO, NO, and NO.

Development of a CRISPR/Cas13a-based electrochemiluminescence biosensing strategy for sensitive detection of α-synuclein oligomers in neurodegenerative diseases.

In this study, we report a highly sensitive CRISPR/Cas13a-based electrochemiluminescence (ECL) biosensor for detecting α-synuclein oligomers, early biomarkers for neurodegenerative diseases. The system integrates aptamer recognition, T7 transcription, CRISPR/Cas13a cleavage, and EXPAR amplification. α-Synuclein binding triggers the release of the T7 promoter, leading to RNA production that activates Cas13a, initiating collateral cleavage and EXPAR, generating double-stranded DNA that interacts with [Ru(phen)₂dppz] to produce a measurable ECL signal.

The disrupted jet stream and its influence on flight time during solar proton events.

The long-chain effects of eruptive solar activities on Earth's magnetosphere, ionosphere, and the mid-to-lower atmospheric circulation are an important theoretical research topic in the fields of space weather and atmospheric science. Understanding the impact of space weather on aviation holds substantial economic value. It is well-known that flight times for polar routes may increase during solar proton events (SPEs) due to the necessity of avoiding high-energy particles.

Research on the proximity relationships of psychosomatic disease knowledge graph modules extracted by large language models.

As social changes accelerate, the incidence of psychosomatic disorders has significantly increased, becoming a major challenge in global health issues. This necessitates an innovative knowledge system and analytical methods to aid in diagnosis and treatment. Here, we establish the ontology model and entity types, using the BERT model and LoRA-tuned LLM for named entity recognition, constructing the knowledge graph with 9668 triples.

Five years of biochar amendment combined with reduced fertilization and irrigation improved the soil organic carbon composition and structure in a solonchak.

Biochar application can increase cultivated soil organic carbon (SOC) and fertility, especially in saline‒alkali soils facing climate change and salinization. To evaluate the effects of biochar application on SOC composition and structure, a 5-year maize field trial (2019-2023) was conducted in the Tarim River Basin, involving seven treatments with the following respective mineral N inputs (kg N ha), irrigation levels (mm) and biochar amendments (t ha): CONTROL (untreated soil), LNLW (100, 140, and 0), LNLWB (100, 140, and 10), MNMW (200, 220, and 0), MNMWB (200, 220, and 10), HNHW (300, 320, and 0), and HNHWB (300, 320, and 10). The SOC characteristics were analyzed after harvest.

Effect of three rhizobacteria on lettuce growth and soil N2O emission and their impact on the rhizosphere bacterial community in acidic field experiments.

Aims: Acidic soils have a high potential for nitrous oxide (N2O) emission. Plant growth-promoting rhizobacteria (PGPR) may mitigate N2O emissions in acidic soils; however, the reduction capacity and their microbiological mechanisms are poorly understood. We investigated the effects of three PGPR strains (Bacillus subtilis subsp.

Multimodal intelligent biosensors framework for fall disease detection and healthcare monitoring.

Introduction: In the field of human action recognition, the fusion of multi-modal data from RGB and inertial modalities provides a valid technique for identifying activities of daily life and falls.

Methods: Our approach uses two reference datasets: UR-Fall Detection and UMA_Fall Detection for ADL and Fall Events. First, data preprocessing is conducted for each sort of sensor individually, then the signals are windowed and segmented properly.

IBDAIM:Artificial intelligence for analyzing intestinal biopsies pathological images for assisted integrated diagnostic of inflammatory bowel disease.

Background: Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is challenging to diagnose accurately from pathological images due to its complex histological features. This study aims to develop an artificial intelligence (AI) model, IBDAIM, to assist pathologists in quickly and accurately diagnosing IBD by analyzing whole-slide images (WSIs) of intestinal biopsies.

Methods: This retrospective cohort study used data from two institutions, Nanjing Drum Tower Hospital (NDTH) and Zhujiang Hospital (ZJH).

Spatiotemporal variations of atmospheric XCH in China based on multiple spatially continuous satellite-derived products.

Spatiotemporally continuous satellite CH column concentrations (XCH) are crucial for accurately assessing variations in atmospheric CH. However, most existing studies rely on single or a limited number of spatiotemporally discontinuous XCH satellite observations. This study evaluates the accuracy of three newly developed spatiotemporally continuous reconstructed XCH products -Song-XCH, Wang-XCH, and Jin-XCH using ground-based data from the Total Carbon Column Observing Network (TCCON) and the World Data Centre for Greenhouse Gases (WDCGG), and analyzes the spatiotemporal variations of XCH across China.

Mesoporous BiS/BiO Heterostructure-Based Sensors for Sub-ppm NO Detection at Room Temperature.

Novel BiS/BiO hybrid materials with unique mesoporous structures were successfully synthesized via a facile in situ elevated-temperature thermal oxidation method using the BiS as a precursor in air. The as-prepared BiS/BiO heterostructure-based sensor exhibits an excellent performance for detecting sub-ppm concentrations of NO at room temperature (RT). In the presence of 8 ppm NO, the sensor registers a response of approximately 7.