Search Results (289)

Soil salinization and selenium (Se) deficiency threaten global food security. This study developed a composite bioinoculant combining ACC deaminase-producing Serratia liquefaciens and biogenically synthesized nano-selenium (SeNPs) to alleviate saline–alkali stress and enhance Se nutrition in rice (Oryza sativa L.). A strain of S. liquefaciens with high ACC deaminase activity was isolated and used to biosynthesize SeNPs with stable physicochemical properties. Pot experiments showed that application of the composite inoculant (S3: S. liquefaciens + 40 mmol/L SeNPs) significantly improved seedling biomass (fresh weight +53.8%, dry weight +60.6%), plant height (+31.6%), and root activity under saline–alkali conditions. S3 treatment also enhanced panicle weight, seed-setting rate, and grain Se content (234.13 μg/kg), meeting national Se-enriched rice standards. Moreover, it increased rhizosphere soil N, P, and K availability and improved microbial α-diversity. This is the first comprehensive demonstration that a synergistic bioformulation of ACC deaminase PGPR and biogenic SeNPs effectively mitigates saline–alkali stress, enhances soil fertility, and enables safe Se biofortification in rice. Full article

Phytoremediation is a green economic method to address soil cadmium (Cd) pollution, and Solanum americanum is considered a potential phytoremediation candidate. However, the underlying Cd response mechanisms of S. americanum remain unclear. In the current study, a hydroponic experiment with 160 μmol/L Cd stress was conducted, physiological and molecular indices were measured to explore the response of S. americanum leaves to Cd stress at different time points (0, 3, and 7 days). Our findings revealed that Cd stress inhibited plant growth. Moreover, Cd stress significantly increased Cd accumulation, as well as Chla content, Chla/b, activities of SOD and POD, and elevated MDA content in the leaves. Furthermore, transcriptomics, proteomics, and metabolomics analyses revealed 17,413 differentially expressed genes (DEGs), 1421 differentially expressed proteins (DEPs), and 229 differentially expressed metabolites (DEMs). Meanwhile, integrative analyses of multi-omics data revealed key proteins involved in response to Cd stress, including POD, PAL, F5H, COMT, and CAD for phenylpropanoid biosynthesis, as well as GAPA, FBP, and FBA for photosynthesis pathways. Additionally, conjoint analyses highlighted that upregulated phenylpropanoid metabolism and photosynthesis alleviated Cd toxicity, playing vital roles in enhancing Cd tolerance in leaves. A conceptual molecular regulatory network of leaves in the response to Cd toxicity was proposed. This comprehensive study will provide detailed molecular-scale insights into the Cd response mechanisms in S. americanum. Full article

Biomass units can play a certain role in peak summer and winter due to their advantages in terms of their environmental and short-term peak ability. To analyze the peak ability of biomass units, this paper focuses on the dynamic modeling of biomass unit peak ability. Firstly, the process of biomass feeding amount to power output is divided into a feed–heat module, heat–main steam pressure module and main steam pressure–power module. A two-input and two-output dynamic model is established where the feeding amount and turbine valve opening serve as inputs, and the main steam pressure and power serve as outputs. Then the effectiveness of the established model is validated by actual operation data of a 30 MW biomass unit. This dynamic model can provide a mechanistic model for analyzing the impact of fuel calorific value on the power output, and provide support for fuel management and scheduling strategies during the peak period of biomass units. Full article

Since its emergence in China in 2018, African swine fever virus (ASFV) has posed a severe threat to the pig farming industry due to its high transmissibility and mortality rate. The clinical signs of ASFV infection often overlap with those caused by other swine viruses such as classical swine fever virus (CSFV), porcine reproductive and respiratory syndrome virus (PRRSV), pseudorabies virus (PRV), and porcine circovirus type 2 (PCV2), making timely and precise diagnosis a considerable challenge. To address this, we established a TaqMan-based multiplex real-time quantitative PCR (qPCR) assay capable of simultaneously detecting ASFV, CSFV, PRRSV, PRV, and PCV2. Specific primer-probe sets were developed targeting conserved genomic regions: the ASFV P72 gene, CSFV 5’UTR region, PRRSV ORF6, PCV2 cap gene, and PRV gB gene. After thorough optimization, the assay demonstrated robust analytical performance, exhibiting strong target specificity with no cross-detection of non-target pathogens. The detection threshold was determined to be 10 copies/μL per virus, indicating high assay sensitivity. Repeatability analysis revealed low variability, with intra- and inter-assay coefficient of variation values remaining below 2.3%. When applied to 95 clinical samples, the multiplex assay yielded results that were fully consistent with those obtained using commercially available singleplex qPCR kits. In conclusion, the multiplex TaqMan qPCR method developed in this study is characterized by high specificity, sensitivity, and reproducibility. It provides a reliable and efficient diagnostic tool for the simultaneous detection and differential diagnosis of ASFV and other clinically similar viral infections in swine, thereby offering robust technical support for swine disease surveillance and control. Full article

Background: The bone morphogenetic protein (BMP) signaling pathway is essential for lung development. BMP4, a key regulator, binds to type I (BMPR1) and type II (BMPR2) receptors to initiate downstream signaling. While the inactivation of Bmpr1a and Bmpr1b leads to tracheoesophageal fistulae, the role of BMPR2 mutations in lung epithelial development remains unclear. Methods: We generated induced pluripotent stem cells (iPSCs) from a patient carrying a BMPR2 mutation (c.631C>T), and gene-corrected isogenic controls were created using CRISPR/Cas9. These iPSCs were differentiated into lung progenitor cells and subsequently cultured to generate alveolar and airway organoids. The differentiation efficiency and epithelial lineage specification were assessed using immunofluorescence, flow cytometry, and qRT-PCR. Results: BMPR2-mutant iPSCs showed no impairment in forming a definitive or anterior foregut endoderm. However, a significant reduction in lung progenitor cell differentiation was observed. Further, while alveolar epithelial differentiation remained largely unaffected, airway organoids derived from BMPR2-mutant cells exhibited impaired goblet and ciliated cell development, with an increase in basal and club cell markers, indicating skewing toward undifferentiated airway cell populations. Conclusions: BMPR2 dysfunction selectively impairs late-stage lung progenitor specification and disrupts airway epithelial maturation, providing new insights into the developmental impacts of BMPR2 mutations. Full article

Elevated [CO₂] enhances light interception and carboxylation efficiency in plants. The combined effects of [CO₂] and photosynthetic photon flux density (PPFD) on stomatal morphology, leaf anatomy, and photosynthetic capacity in tomato seedlings remain unclear. This study subjected tomato seedlings (Solanum lycopersicum Mill. cv. Jingpeng No.1) to two [CO₂] (ambient [a[CO₂], 400 µmol·mol⁻¹] and enriched [e[CO₂], 800 µmol·mol⁻¹]) and three PPFD levels (L; low[Ll: 200 µmol·m⁻²·s⁻¹], moderate[Lm: 300 µmol·m⁻²·s⁻¹], and high[Lh: 400 µmol·m⁻²·s⁻¹]) to assess their interactive impacts. Results showed that e[CO₂] and increased PPFD synergistically improved relative growth rate and net assimilation rate while reducing specific leaf area and leaf area ratio. Notably, e[CO₂] decreased stomatal aperture (−13.81%) and density (−27.76%), whereas elevated PPFD promoted stomatal morphological adjustments. Additionally, Leaf thickness increased by 72.98% under e[CO₂], with Lm and Lh enhancing this by 10.79% and 41.50% compared to Ll. Furthermore, photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). While both e[CO₂] and increased PPFD Photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). Moreover, e[CO₂]-Lh treatment maximized total dry mass and seedling health index. Correlation analysis indicated that synergistic optimization of stomatal traits and leaf structure under a combination of e[CO₂] and increased PPFD enhanced light harvesting and CO₂ diffusion, thereby promoting carbon assimilation. These findings highlight e[CO₂]-Lh as an optimal strategy for tomato seedling growth, providing empirical guidance for precision CO₂ fertilization and light management in controlled cultivation. Full article

The migration of hindered phenolic antioxidants from food contact materials (FCMs) into foodstuffs poses health risks due to endocrine disruption and organ toxicity. Hence, the development of a high-efficiency analytical method for hindered phenolic antioxidants is of great importance for food safety. This study developed a novel ultrasound-assisted dispersive solid-phase filter extraction (d-SPFE) coupled with green supercritical fluid chromatography (SFC) method for the simultaneous determination of six representative hindered phenolic antioxidants. Under optimized conditions, the method achieved high extraction efficiency, with the complete separation of all analytes within 10 min. A wide linearity range (0.02–2.0 μg/mL) was achieved, with coefficients of determination all greater than 0.9996. The limits of detection (LOD, S/N = 3) and limits of quantification (LOQ, S/N = 10) were 2.4–3.6 ng/mL and 8–12 ng/mL, respectively. Validation tests demonstrated precise spiked recoveries (89.4–101.6%), with intra-day and inter-day relative standard deviations (RSDs) all less than 10%. The d-SPFE-SFC synergy significantly outperforms conventional techniques in terms of analysis speed and eco-efficiency. Successful application to food simulants confirms its reliability in monitoring hindered phenolic antioxidant migration from FCMs. This green and rapid methodology will enable the direct assessment of migration risks. Full article

Background: The limited bioavailability of free phytosterols restricts their clinical application in managing hypercholesterolemia. This study aimed to develop phytosterol nanoparticles (PNs) to enhance bioactivity and investigate their cholesterol-lowering efficacy and underlying mechanisms in vivo. Methods: Phytosterol nanoparticles (PNs) (93.35 nm) were engineered using soy protein isolate and administered orally at concentrations of 4.00–12.50 mg/mL to high-fat-diet-induced hypercholesterolemic mice (n = 60) over a 4-week period. Serum and hepatic lipid profiles, histopathology, gene/protein expression related to cholesterol metabolism, and fecal sterol content were evaluated. Results: PNs dose-dependently reduced serum total cholesterol (TC: 28.6–36.8%), triglycerides (TG: 22.4–30.1%), and LDL-C (31.2–39.5%), while increasing HDL-C by 18.7–23.4% compared to hyperlipidemic controls (p < 0.01). Hepatic TC and TG accumulation decreased by 34.2% and 41.7%, respectively, at the highest dose, with histopathology confirming attenuated fatty degeneration. Mechanistically, PNs simultaneously suppressed cholesterol synthesis through downregulating HMGCR (3.2-fold) and SREBP2 (2.8-fold), while enhancing cholesterol catabolism via CYP7A1 upregulation (2.1-fold) at protein level. Although less potent than simvastatin (p < 0.05), the nanoparticles exhibited unique dual-pathway modulation absent in conventional phytosterol formulations. Fecal analysis revealed dose-responsive cholesterol excretion (36.01 vs. 11.79 mg/g in controls), indicating enhanced enteric elimination. While slightly less potent than simvastatin (p < 0.05), PNs offered unique dual-pathway modulation absent in conventional phytosterol formulations. Conclusions: Nano-encapsulation significantly improves the bioavailability and hypocholesterolemic efficacy of phytosterols. PNs represent a promising nutraceutical strategy for cholesterol management by concurrently regulating cholesterol synthesis and catabolism, with potential application in both preventive and therapeutic contexts. Full article

A reliable ocean surface current (OSC) estimate is difficult to retrieve from synthetic aperture radar (SAR) data due to the challenge of accurately partitioning the Doppler shifts induced by wind waves and OSC. Recent research on SAR-based OSC retrieval is typically based on the assumption that the SAR Doppler shifts caused by wind waves and OSC are linearly superimposed. However, this assumption may lead to large errors in regions where nonlinear wave–current interactions are significant. To address this issue, we developed a novel deep learning model, OSCNet, for OSC retrieval. The model leverages Sentinel-1 Interferometric Wide (IW) Level 2 Ocean products collected from July 2023 to September 2024, combined with wave data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and geostrophic currents from newly available SWOT Level 3 products. The OSCNet model is optimized by refining input ocean surface physical parameters and introducing a ResNet structure. Moreover, the Normalized Radar Cross-Section (NRCS) is incorporated to account for wave breaking and backscatter effects on Doppler shift estimates. The retrieval performance of the OSCNet model is evaluated using SWOT data. The mean absolute error (MAE) and root mean square error (RMSE) are found to be 0.15 m/s and 0.19 m/s, respectively. This result demonstrates that the OSCNet model enhances the retrieval of OSC from SAR data. Furthermore, a mesoscale eddy detected in the OSC map retrieved by OSCNet is consistent with the collocated sea surface chlorophyll-a observation, demonstrating the capability of the proposed method in capturing the variability of mesoscale eddies. Full article

Background: Pulmonary fibrosis (PF) is a progressive interstitial lung disease characterized by chronic inflammation and excessive extracellular matrix deposition, with fibrocytes playing a pivotal role in fibrotic remodeling. This study aimed to identify upstream molecular mechanisms regulating fibrocyte recruitment and activation, focusing on the SPHK1 pathway as a potential therapeutic target. Methods: We utilized Mendelian Randomization and phenome-wide association analyses on genes involved in sphingolipid metabolism to identify potential regulators of idiopathic pulmonary fibrosis (IPF). A bleomycin-induced mouse model was employed to examine the role of the SPHK1-S1P axis in fibrocyte recruitment, using SKI-349 to target SPHK1 and FTY720 to antagonize S1PR1. Results: Our analyses revealed SPHK1 as a significant genetic driver of IPF. Targeting SPHK1 and S1PR1 led to a marked reduction in fibrocyte accumulation, collagen deposition, and histopathological fibrosis. Additionally, PAXX and RBKS were identified as downstream effectors of SPHK1. Our protein–protein interaction mapping indicated potential therapeutic synergies with existing anti-fibrotic drug targets. Conclusions: Our findings establish the SPHK1-S1P-S1PR1 axis as a key regulator of fibrocyte-mediated pulmonary fibrosis and support SPHK1 as a promising therapeutic target. Full article

Melicope pteleifolia (Rutaceae) is a shrub or tree with high medicinal value. Although the physical features of M. pteleifolia are evident, the mitochondrial (mt) genome has yet to be investigated, and its evolutionary relationship within Rutaceae is unclear. The organelle genomes of M. pteleifolia were constructed using Nanopore and Illumina sequencing data. The circular mt genome is 780,107 base pairs (bp) long, with a GC content of 44.85%. It has 66 genes, consisting of 33 protein-coding genes (PCGs), 30 tRNA genes, and 3 rRNA genes. The length of the chloroplast (cp) genome was 158,987 bp, containing 88 PCGs, 37 tRNAs, and 8 rRNAs. The mtDNA and cpDNA contained 507 and 353 repetitive sequences, respectively. RNA editing sites were abundant in M. pteleifolia organelle genomes, including 323 sites in mtDNA and 260 sites in cpDNA. Phylogenetic research using the cp and mt genomes of M. pteleifolia and nine additional species of the Rutaceae family precisely delineates its evolutionary and taxonomic position. Ka/Ks and nucleotide diversity indicated that the majority of the PCGs in the mitochondrial genome had experienced negative selection. These findings provided comprehensive information on the M. pteleifolia mitogenome for studying phylogenetic relationships in Rutaceae, with chloroplast-derived sequences providing critical evidence for inter-organellar genome evolution. Full article

Federated learning is a distributed machine learning framework that allows multiple clients to collaborate on training global models without sharing raw data, thereby protecting data privacy. However, it is still a challenge to construct an efficient federated learning method for the semantic segmentation task of automated driving street view. On the one hand, the complexity of the semantic segmentation model is high, resulting in huge computing and communication overhead of client local training. On the other hand, the client data distribution is significantly different and has Non-Independent and Identically Distributed (non-IID) characteristics, which easily leads to the difficulty of global model convergence or the deterioration of generalization performance. Therefore, this paper proposes a Federal Street View segmentation method, Federal Street View Segmentation (FedSS), which optimizes model training by improving the cross-entropy loss function and designing a gradient compensation strategy and a gradient sparse compression strategy to alleviate the high communication overhead in federation learning. Extensive experiments show that our approach can consume fewer computational resources and achieve higher communication efficiency while improving semantic segmentation performance. Full article

Angiotensin II receptor blockers (ARBs), a critical class of second-generation antihypertensive drugs, require azide intermediates for constructing their biphenyl tetrazole pharmacophore. This synthetic reaction introduces hypertoxicity risks, as residual azides can induce fatal damage even at trace concentrations. The pharmacopoeias of most countries have highlighted the urgency for improved detection paradigms of the control of azides in ARBs. Current ion chromatography (IC) methods face analytical challenges due to matrix interference from organic solvents and incompatibility with hydrophobic ARB ingredients. Herein, an in situ matrix elimination ion chromatography methodology was established for the sensitive detection of trace azides in angiotensin II receptor blocker pharmaceuticals. The switching strategy used in the proposed methodology eliminates organic interference and avoids the incompatibility issue with ARB ingredients. Under the optimal conditions, the proposed method exhibited satisfactory linearity in the range of 2.0–200.0 ng/mL, with a correlation coefficient of 0.9996. Validation studies demonstrated a detection limit (LOD, S/N = 3) of 0.57 ng/mL and a quantification limit (LOQ, S/N = 10) of 1.89 ng/mL, surpassing the sensitivity requirements in pharmacopeias. Method robustness was confirmed, with recovery rates from 92.8 to 108.7% using spiked ARBs real samples, and the intra-day and inter-day RSDs were less than 9.7%. The proposed approach establishes a reliable, precise, and sensitive alternative for monitoring azide impurities in ARBs, and such a framework can overcome limitations such as solubility issues, contributing to a universal applicability to diverse hydrophobic drugs. Full article

To address the multi-target detection problem in the automatic seedling-feeding procedure of vegetable-grafting robots from dual perspectives (top-view and side-view), this paper proposes an improved YOLOv8-SDC detection segmentation model based on YOLOv8n-seg. The model improves rootstock seedlings’ detection and segmentation accuracy by SAConv replacing the original Conv c2f_DWRSeg module, replacing the c2f module, and adding the CA mechanism. Specifically, the SAConv module dynamically adjusts the receptive field of convolutional kernels to enhance the model’s capability in extracting seedling shape features. Additionally, the DWR module enables the network to more flexibly adapt to the perception accuracy of different cotyledons, growth points, stem edges, and contours. Furthermore, the incorporated CA mechanism helps the model eliminate background interference for better localization and identification of seedling grafting characteristics. The improved model was trained and validated using preprocessed data. The experimental results show that YOLOv8-SDC achieves significant accuracy improvements over the original YOLOv8n-seg model, YOLACT, Mask R-CNN, YOLOv5, and YOLOv11 in both object detection and instance segmentation tasks under top-view and side-view conditions. The mAP of Box and Mask for cotyledon (leaf1, leaf2, leaf), growing point (pot), and seedling stem (stem) assays reached 98.6% and 99.1%, respectively. The processing speed reached 200 FPS. The feasibility of the proposed method was further validated through grafting features, such as cotyledon deflection angles and stem–cotyledon separation points. These findings provide robust technical support for developing an automatic seedling-feeding mechanism in grafting robotics. Full article