Search Results (1,622)

Biochar can improve soil physicochemical properties and microbial habitats; however, its application rate-dependent effects in maize fields of the black soil region remain insufficiently understood under field conditions. A three-year field experiment was conducted in Jiamusi, Heilongjiang Province, China, from 2023 to 2025, with four biochar application rates: 0 (W0), 10 (W1), 20 (W2), and 40 t ha⁻¹ (W3). Soil physicochemical properties, bacterial communities based on 16S rRNA gene sequencing, and fungal communities based on internal transcribed spacer (ITS) sequencing were analyzed to assess changes in soil fertility and microbial community composition and their relationships with environmental factors. Biochar application significantly increased soil organic matter, alkali-hydrolyzable nitrogen, available potassium, and pH. Although W3 produced the greatest nutrient enhancement, W2 exhibited a more balanced overall response across the measured soil fertility and microbial community indicators. Sequencing depth was adequate for all samples, and bacterial alpha diversity was comparatively well maintained under W2 and W3. Fungal alpha diversity exhibited pronounced interannual variation and increased under W3 in 2025. Year accounted for a greater proportion of variation in microbial community structure than did biochar treatment; however, both treatment and the year × treatment interaction also had significant effects. Among the measured soil fertility and microbial community indicators, W2 produced a comparatively balanced overall response, whereas W3 exerted stronger selective effects on microbial communities. Because crop yield, economic feasibility, labile carbon fractions, and long-term ecological outcomes were not assessed, an agronomically optimal biochar application rate cannot yet be determined. Full article

Although commercial vaccines against porcine circovirus type 2 (PCV2) have been widely implemented globally, PCV2 remains endemic in swine populations, accompanied by ongoing genotype replacement. Meanwhile, the emergence of novel porcine circoviruses (PCVs), including PCV3 and PCV4, has further complicated the prevention and control of porcine circovirus-associated diseases (PCVAD). This study systematically characterized the epidemiological patterns and genetic diversity of PCVs circulating in Eastern China. A total of 739 clinical samples collected between 2010 and 2016 were screened for PCV2. Additionally, 653 samples obtained during 2023–2024 were analyzed using a triplex real-time quantitative PCR (qPCR) assay for the simultaneous detection of PCV2, PCV3, and PCV4. Full-genome amplification and sequencing were subsequently performed on all PCR-positive samples. Epidemiological analysis revealed an overall PCV2 positivity rate of 37.62% during 2010–2016. In the 2023–2024 cohort, the positivity rates for PCV2 and PCV3 were 35.99% and 16.39%, respectively, with a co-infection rate of 10.26%. Notably, no PCV4-positive samples were detected. Phylogenetic analysis demonstrated that PCV2d is the predominant genotype in Eastern China. Furthermore, PCV2g strains were identified in clinical samples for the first time in mainland China, while PCV3b were determined to be the dominant circulating subtype of PCV3. Multiple critical amino acid substitutions were identified within the neutralizing epitopes of the PCV2 Cap protein, and a recombination event involving a PCV2d vaccine strain and a PCV2c reference strain was detected. In contrast, the PCV3 genome exhibited a high degree of genetic conservation. Collectively, these findings expand the molecular epidemiological landscape of PCVs in Eastern China and elucidate the evolutionary dynamics of circulating PCV strains, providing important insights for the development of next-generation vaccines and region-specific PCVAD control strategies. Full article

This study examines the impact of agricultural insurance on farm household resilience and explores the underlying mechanisms through which this effect operates. Using survey data from 1242 farm households collected in 2021 across three major grain-producing provinces in China—Heilongjiang, Henan, and Hunan—this study constructs a multidimensional index of household resilience based on resistance, recovery, and regeneration using the entropy method. An instrumental variable approach is employed to address endogeneity concerns, and a mediation model is used to identify the mechanisms of influence. The results show that agricultural insurance significantly enhances farm household resilience, with the strongest effect observed in the recovery dimension. Mechanism analysis reveals that this effect operates through reducing risk aversion, improving income security, and promoting crop innovation. Heterogeneity analysis indicates that the resilience-enhancing effect is more pronounced among large-scale farmers and those who have not adopted climate adaptation measures. These findings suggest that agricultural insurance plays a critical role in strengthening farm household resilience through multiple channels. Policy efforts should focus on improving insurance accessibility, particularly for smallholder farmers, and promoting complementary measures such as risk management education and technological innovation. Full article

Global atmospheric N₂O concentrations have risen to 335 ppb, with agricultural soils serving as a major emission source and rice paddies accounting for approximately 11% of agricultural N₂O emissions. Rice–crab co-culture has been widely adopted because of its potential to increase and stabilize crop yields; however, the underlying mechanisms of N₂O mitigation and the synergistic effects of crab bioturbation with water and nitrogen management remain unclear. Therefore, in this study, we conducted a two-year field experiment in Zhaodong, Heilongjiang Province, China, to elucidate the N₂O mitigation effects of rice–crab co-culture under water and nitrogen regulation and the associated driving mechanisms. The results showed that rice–crab co-culture significantly reduced N₂O emissions. Specifically, the N₂O flux decreased by 19.9%, while cumulative N₂O emissions decreased by 19.8%. Under the combined regulation of water and nitrogen management, the mitigation effect on N₂O emissions was further enhanced, with a reduction of up to 30.8%. Regarding environmental factors, crab activity combined with shallow wet irrigation reduced soil water content and increased surface temperature. These changes promoted the transformation of nitrogen from inorganic forms to microbially assimilable forms, increasing the microbial nitrogen content by approximately 29.5%. Meanwhile, soil enzyme activities changed significantly: the activities of urease, sucrase, and protease increased, whereas nitrate reductase activity decreased. Structural equation modeling showed that the indirect effect of management practices was much greater than the direct effect, accounting for 63% of the total effect. Nitrogen transformation was the core mitigation pathway, characterized by the conversion of inorganic nitrogen into microbial biomass nitrogen, which reduced substrate availability for nitrification and denitrification. Enzyme activity regulation served as a secondary pathway, mainly through the inhibition of nitrate reductase activity. Overall, the rice–crab system achieved sustained N₂O reduction by improving soil aeration and jointly regulating substrate limitation and weakening nitrogen transformation capacity. Full article

To address the limitations of existing low-temperature evaluation methods for battery electric vehicles (BEVs) in terms of real-world road adaptability, test consistency, and multidimensional performance assessment, this study proposes a standardized on-road testing and multidimensional adaptability evaluation system for BEVs in frigid environments. To address the issues that conventional bench tests cannot adequately replicate real-world road environments, routine road tests lack consistency, and existing evaluation indicators pay insufficient attention to charging efficiency and cabin heating performance, this study defines the ambient temperature for road testing, low-speed steady-state driving conditions, and the conditions for ensuring consistency in road testing. It also establishes a cold-environment adaptability evaluation system comprising three dimensions—driving range, charging efficiency, and heating, ventilation, and air conditioning (HVAC) heating performance—and four evaluation indicators: the driving range degradation rate in cold environments, charging time per 100 km, HVAC heating duration, and HVAC heating energy consumption per unit cabin volume. Field tests were conducted on 10 representative BEVs in real-world road conditions near −20 °C in Heihe City, Heilongjiang Province, China. The results indicate that the average range degradation rate for these 10 models in cold environments was 60.7%, and approximately 60% of the vehicles could complete a 100 km charge in under 30 min; the average HVAC heating time was 34 min, with an average power consumption of 9.2 kWh. The tests also revealed that the heating efficiency and thermal comfort of single-heat-pump HVAC systems at −20 °C still have room for improvement, and that the uniformity of cabin temperature distribution and consistency in foot temperature between the left and right sides significantly affect thermal comfort. The evaluation method proposed in this study can serve as a reference for testing the cold-weather adaptability of BEVs, as well as for optimizing thermal management systems and developing vehicle performance. Full article

Sustaining rice productivity under the dual constraints of freshwater scarcity and low-temperature stress represents a pressing challenge for high-latitude japonica rice systems worldwide. There is an urgent need to develop coupled irrigation–agronomic management strategies that jointly safeguard yield stability and water use efficiency (WUE) in cold-region rice production. In this study, a two-year field experiment was conducted in 2024–2025 on albic soil (Albic Luvisols, WRB; θfc 38.2% v/v, pH 5.80, clayey texture with poor permeability and a propensity for subsurface waterlogging) in the Sanjiang Plain, Heilongjiang Province, China (47°15′ N, 133°28′ E), with nine coupled “irrigation regime × auxiliary practice” treatments, comprising conventional continuous flooding, four-level controlled irrigation (CI) at lower thresholds of 60%, 70%, 75%, and 80% θfc, and their combinations with film mulching (FM) or a humic-acid-based soil amendment (SA). An interpretable machine-learning diagnostic framework was developed, with elastic net (EN) as the primary analytical model and random forest (RF) as a nonlinear control, to simultaneously identify core yield predictors and outlier treatments. The principal findings were: (i) The soil-amendment-coupled 75% θfc CI treatment (SACI) increased grain yield by 12.3% and reduced water input by 17.0% relative to conventional continuous flooding, with WUE reaching 1.801 kg m⁻³, a 35.3% gain over the control (p < 0.05); these improvements were consistent across both individual years (year × treatment interaction: p = 0.601; inter-year rank correlation ρ = 0.967). Lowering the CI threshold below 75% θfc significantly reduced grain yield through diminished effective-panicle retention. (ii) Multi-method consensus analysis (Kendall’s W = 0.871, p < 0.01) identified root volume at the milk stage as the most strongly and consistently associated statistical predictor of yield formation, with convergent mechanistic support from independent rhizosphere evidence (Eh, TTC reductive activity). Definitive causal validation awaits isotope-tracing experiments. (iii) The film-mulching × continuous-flooding treatment (FMCG) was diagnosed as a yield-response outlier (permutation test p = 0.003), three in situ rhizosphere measurements (redox potential, root TTC-reducing activity, and rhizosphere temperature) supported the proposed mechanism of hot–anoxic rhizospheric inhibition. Methodologically, this study develops a four-level evidence convergence framework that integrates intra-model self-consistency, cross-model (EN vs. RF) consensus, independent rhizosphere evidence, and distribution-free permutation testing, with Jackknife+ conformal prediction and companion Monte Carlo simulations (1000 replicates) used to quantify the reliability boundaries under small-sample conditions (n = 27). These findings provide an evidence-based irrigation–soil co-management strategy for cold-region rice production in Northeast China, and the proposed diagnostic paradigm offers a generalizable, reliability-quantified methodological template for interpretable small-sample modeling in multifactorial coupled field experiments. Full article

Anthropogenic land-use change influences soil organic carbon (SOC) dynamics by altering both biotic and abiotic soil factors. The carbon stable isotope ratio of SOC (δ¹³C) indicates the vegetation sources of organic carbon and legacy effects of historical land use, providing important information for carbon dynamics. However, the mechanisms driving SOC dynamics in deep soils (>100 cm) under different land cover and land-use types remain poorly understood. Here, we analyzed the SOC content and δ¹³C in thick soil profiles (a thickness of 160 cm or 200 cm) under different land cover/land-use types in the typical black soil region of the Songnen Plain, Northeast China. The results showed that the average SOC content at 0–30 cm depth in natural forest land (38.87 g kg⁻¹) was higher than that in the forest land converted to cultivated land (31.66 g kg⁻¹), artificial forest land (22.63 g kg⁻¹), and perennial cultivated land (18.16 g kg⁻¹). Similarly, the average SOC content below 100 cm depth was higher in natural forest land (7.99 g kg⁻¹) than in artificial forest land (6.90 g kg⁻¹), the conversion of natural forest to cropland (6.59 g kg⁻¹), and perennial cultivated land (4.39 g kg⁻¹). Notably, significant positive correlations between δ¹³C and SOC were observed in both natural forest land and perennial cultivated land, presenting the synergistic effects on SOC probably influenced by carbon input, microbial communities, and environmental conditions. Further investigation revealed that soil moisture content and pH significantly influenced SOC content, probably by regulating organic matter decomposition rates. The natural forest land with high moisture content and low pH conditions created favorable environments for carbon preservation, whereas long-term cultivated cropland with low moisture content and high pH conditions accelerated carbon mineralization processes. These results indicate that land cover and land-use change not only significantly alter surface SOC content but also drive deep soil carbon cycling dynamics by regulating soil moisture content, pH and δ¹³C values. This study elucidates the intrinsic relationships between SOC content, δ¹³C, pH, and moisture content under land-use change, providing scientific support for land use-aware carbon management strategies in black soil regions. Full article

Wood- and lignocellulosic-residue-derived constituents have attracted increasing attention in cementitious materials because they may support clinker reduction, waste valorization, moisture regulation, crack control, and longer service life. This review synthesizes evidence on wood ash, wood-derived biochar, and wood or lignocellulosic fibers in low-clinker and low-carbon-oriented cementitious systems, with emphasis on severe cold service involving freeze–thaw cycling, salt freezing, and chloride ingress. This review clarifies the evidence boundaries among direct wood-derived materials and related biomass or lignocellulosic analogues, because wood ash, non-wood biomass ashes, such as bamboo ash and bagasse ash, wood fiber, and non-wood plant fibers cannot be treated as equivalent materials. Wood ash is best regarded as a controlled partial binder replacement or filler whose performance depends on combustion temperature, oxide composition, alkali content, residual carbon, fineness, and water demand. Biochar is more appropriately treated as a low-dosage functional additive, commonly in the range of approximately 1–3 wt.% of binder, where it may assist internal curing, nucleation, moisture redistribution, and pore regulation; excessive dosage can increase porosity and reduce mechanical or transport performance. Wood and lignocellulosic fibers mainly contribute to crack control, toughness, and post-cracking behavior, but their effectiveness is limited by water absorption, swelling, lignin- and extractive-related hydration interference, and long-term interfacial degradation in alkaline matrices. Across these material classes, engineering performance is governed by the interfacial transition zone, pore-size distribution, moisture state, air–void compatibility, and exposure-specific durability response. The main contribution of this review is to propose a boundary-conscious framework for material classification, quantitative comparison, mixture-design screening, and severe-cold durability qualification. Future application requires source-specific characterization, water-demand control, treated fibers, low-dosage biochar optimization, and service-informed testing that couples freeze–thaw cycling, chloride transport, saturation state, and microstructural verification. Full article

Advanced oxidation processes (AOPs) are widely applied to degrade recalcitrant organic contaminants in municipal effluents, industrial wastewaters, and water-reuse streams. Their deployment, however, remains constrained by matrix scavenging, high energy or reagent demand, catalyst/electrode ageing, and the possible formation of toxic transformation products. Artificial intelligence and machine learning (AI/ML) have been proposed as tools for prediction, optimization, catalyst discovery, mechanism inference, and process control, but high accuracy on curated laboratory datasets is often confused with actionable knowledge for real treatment systems. This narrative review evaluates AI/ML-enabled AOPs through an evidence-to-deployment framework built on three principles: real wastewater is treated as the primary inference domain; mechanistic claims are graded according to convergent evidence; and AI/ML contributions are linked to explicit decisions rather than to model accuracy alone. We argue that progress depends less on black-box complexity than on standardized reporting, benchmark matrices, curated datasets, uncertainty-aware validation, and pilot-scale demonstrations that satisfy contaminant removal, energy efficiency, byproduct safety, and operational constraints simultaneously. A six-gate decision framework and a targeted research agenda are proposed to guide future studies toward deployment-grade evidence. Full article

Drought is one of the most complex and impactful natural hazards under global climate change, exerting profound effects on water resources, agricultural productivity, ecosystem stability, and socio-economic systems. Despite extensive research, current drought studies remain fragmented due to inconsistent definitions, index-specific monitoring approaches, and limited understanding of cross-variable and cross-scale interactions. The objective of this review is to synthesize recent advances in drought monitoring and to establish an integrated understanding of drought as a coupled, multiscale process. We revisit traditional drought typologies, including meteorological, agricultural, hydrological, groundwater drought, and socio-economic drought, and critically evaluate their commonly used monitoring indices and data sources. We highlight that no single indicator can adequately capture the full dynamics of drought evolution, emphasizing the need for multi-index integration and process-based monitoring frameworks. Moreover, we examine the mechanisms of drought propagation, demonstrating that drought evolves through nonlinear and scale-dependent pathways linking atmospheric conditions, soil moisture, hydrological processes, and human water use. In particular, the emergence of flash drought reveals a shift from conventional water-deficit-driven processes to multi-process coupled dynamics, posing new challenges for early warning and prediction. Furthermore, we discuss how climate change and human activities jointly reshape drought characteristics by altering hydrological cycles, land–atmosphere interactions, and water resource management systems. The review reveals three major findings. First, drought monitoring is progressively shifting from single-index assessments toward integrated, multi-source monitoring frameworks. Second, drought propagation is inherently nonlinear and scale-dependent, involving complex interactions among climatic, hydrological, ecological, and human systems. Third, flash drought and groundwater drought have emerged as critical research frontiers due to their rapid evolution, monitoring challenges, and increasing impacts under climate change. Finally, we identify key challenges in drought research, including methodological uncertainties, data limitations, and the lack of a unified theoretical framework. These findings support a paradigm shift from traditional drought classification toward an integrated process-based perspective and provide guidance for the development of next-generation drought monitoring and early-warning systems. Full article

Bioactive peptides have health benefits, but the intense bitterness associated with their hydrolysis severely restricts their industrial applications. This paper systematically constructs a collaborative theoretical framework that integrates intelligent prediction, targeted debittering, and multi-dimensional evaluation. Firstly, it reviews the core applications of deep learning (such as quantitative structure–activity relationship (QSAR) and graph convolutional network (GCN)) combined with molecular docking technology in the high-throughput identification of bitter peptides and the analysis of target receptor interaction mechanisms. Secondly, it discusses how artificial intelligence and computational simulation can improve the efficiency of traditional debittering processes, emphasizing the advantages of multifunctional composite wall materials in the targeted encapsulation and delivery of bitter peptides, as well as the metabolic regulatory mechanisms behind controlling microbial fermentation for the debittering of specific peptide substrates. Finally, to provide a high-fidelity data closed loop for artificial intelligence (AI) models, a three-dimensional cross-validation system integrating standardized quantitative sensory evaluation and biomimetic electronic tongues was established. Future research should focus on developing large models for flavor generation to drive the green and targeted creation of low-bitterness and highly active peptides. Full article

Cold stress is a key environmental constraint in aquaculture, but integrated host responses linking oxidative status, intestinal microbiota, and hepatic metabolism remain insufficiently characterized in Luciobarbus capito. This study aimed to evaluate the biochemical, microbial, and metabolic responses of L. capito to acute low-temperature exposure. Fish were exposed to 12 °C for 96 h, with fish maintained at 22 °C as controls; hepatic antioxidant indices, serum biochemical parameters, intestinal microbiota based on 16S rRNA gene sequencing, and liver metabolomic profiles were analyzed. Cold exposure reduced hepatic total superoxide dismutase (T-SOD) and catalase (CAT) activities and increased malondialdehyde (MDA) content, while serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities increased and acid phosphatase (ACP) activity decreased. The intestinal microbiota showed reduced richness and compositional shifts, including decreased Cetobacterium and increased Pseudomonas. Liver metabolomics identified 172 differential metabolites, with enriched pathways related to glycerophospholipid metabolism, α-linolenic acid metabolism, pantothenate and CoA biosynthesis, and ascorbate and aldarate metabolism. Correlation analysis indicated significant associations between altered bacterial genera and hepatic metabolites. These results suggest that acute cold stress disrupts oxidative balance, intestinal microbial composition, and hepatic metabolism in L. capito, providing an integrated view of associated physiological and metabolic responses to low-temperature stress. Full article

Background/Objectives: Glioblastoma multiforme (GBM) treatment is limited by tumor hypoxia and poor specificity of therapeutic agents. To address these challenges, we developed brain-targeted liposomes co-encapsulating 5-aminolevulinic acid (5-ALA) and catalase (CAT), termed brain-targeted 5-ALA-CAT liposomes (BACL), which were surface-modified with the Angiopep-2 ligand to enhance blood–brain barrier penetration and achieve multimodal therapy combining targeted delivery and oxygen generation. Methods: BACL was prepared and characterized. Tumor targeting was verified by flow cytometry and in vivo imaging. In vitro antitumor activity was evaluated by wound-healing assay, colony formation assay, live/dead staining, MTT assay, and Western blotting. In vivo efficacy, apoptosis, and safety were assessed in a subcutaneous xenograft model. Transcriptome sequencing and qRT-PCR were employed to identify molecular mechanisms and novel targets. Results: BACL exhibited favorable physicochemical properties (size: 122.4 nm, PDI: 0.189, zeta potential: −12.3 mV) and spherical morphology as observed by TEM, with encapsulation efficiencies of 51.2% for 5-ALA and 43.8% for CAT. Compared with unmodified 5-ALA, BACL increased the cellular uptake efficiency by 1.6-fold in glioma cells while maintaining catalytic stability for sustained oxygen generation. In vitro experiments demonstrated that BACL significantly inhibited glioma cell migration, colony formation, and cell viability, and induced apoptosis. In a subcutaneous xenograft tumor model, BACL-mediated photodynamic therapy (PDT) achieved a tumor growth inhibition rate of 52%, with apoptosis induction via regulation of Bcl-2, Bax, and p53 expression, and no obvious toxicity to major organs was observed. Transcriptomic analysis combined with qRT-PCR validation revealed that BACL activates multiple antitumor signaling pathways, including targeted inhibition of IL-10 and CXCL13 to disrupt cytokine–receptor interactions, as well as coordinated regulation of S100A3 and IGSF-9 expression to suppress glioma progression. Conclusions: These multimodal actions enhanced PDT efficacy while remodeling the tumor microenvironment. Our findings position BACL as a promising therapeutic platform integrating targeted delivery, hypoxia alleviation, and immunomodulation for GBM therapy. Full article

Background: Titanium implant osseointegration is hierarchically governed by surface properties directing protein adsorption, cell recognition, immune modulation, and bone formation. Photofunctionalization creates ultrahydrophilic surfaces by removing hydrocarbons. To integrate it with 3D-printed architectures requires systematic synthesis. Problem: The classical static view of osseointegration obscures its dynamic, multiscale nature. How photofunctionalization-induced ultrahydrophilicity modulates the surface–protein–cell–bone interface as a continuous, hierarchical system remains unclear. Scope: This review synthesizes evidence on how photofunctionalized ultrahydrophilic titanium surfaces control protein adsorption, integrin-mediated mechanotransduction, immune responses, and in vivo osseointegration, with an emphasis on 3D-printed porous architectures. Conclusions: Photofunctionalization enhances protein adsorption, preserves bioactive conformation, and stabilizes protein layers, selectively engaging osteogenic integrins and amplifying FAK–Src/YAP–TAZ signaling. In 3D-printed implants, ultrahydrophilicity enables capillary-driven fluid infiltration and uniform bone ingrowth. Through this review, knowledge gaps—in surface aging and limited in situ characterization—are identified, and an interface-informed design integrating surface chemistry, architecture, and biological timing is proposed. Full article

Type 2 diabetes mellitus (T2DM) accounts for over 90% of diabetes cases, and T2DM-related sarcopenia is a growing concern. Carnosine, abundant in human skeletal muscle, helps maintain muscle quality and function. This study investigated whether carnosine deficiency contributes to T2DM-related sarcopenia and whether exogenous carnosine supplementation alleviates muscle atrophy. A mouse model of T2DM sarcopenia was established using streptozotocin combined with a high-fat diet. LC-MS metabolomics revealed a significant reduction in carnosine content in the gastrocnemius muscle of model mice. A C2C12 myotube atrophy model was induced by high-glucose (HG), and qRT-PCR showed altered expression of carnosine metabolism-related enzymes, suggesting disrupted carnosine homeostasis under T2DM conditions. Mechanistic investigations using immunofluorescence, Western blotting, transcriptome sequencing, mitochondrial staining, and molecular docking indicated that carnosine may alleviate high-glucose-induced myotube atrophy through the PI3K/AMPK/PGC-1α signaling pathway. In vivo, carnosine supplementation increased the number of mitochondria and the proportion of slow muscle fibers in gastrocnemius muscle, ameliorating the atrophic phenotype. These findings suggest that carnosine has potential as a candidate for intervention in T2DM-related sarcopenia, though further validation of its direct molecular targets is required. Full article