Search Results (477)

Background/Objectives: Severe coronavirus disease 2019 (COVID-19) is characterized by dysregulated immune activation and excessive inflammation; however, the specific immune cell states that drive disease progression remain incompletely understood. Methods: Here, we integrated single-cell RNA sequencing analysis of peripheral blood mononuclear cells with clinical validation to investigate the role of Ninjurin-1 (NINJ1) in COVID-19-associated immune dysregulation. Results: Single-cell profiling revealed that NINJ1 expression was largely confined to monocytes and defined as a distinct NINJ1⁺ inflammatory monocyte state in patients with COVID-19. Compared with NINJ1⁻ monocytes, NINJ1⁺ monocytes exhibited enhanced inflammatory transcriptional programs, altered regulon activity, and increased cell–cell communication capacity, suggesting their potential role as a highly activated immune state involved in inflammatory amplification. Further ligand–receptor interaction analysis demonstrated that NINJ1⁺ monocytes functioned as key communication hubs within the COVID-19 immune landscape, coordinating extensive interactions with other immune populations. In an independent cohort of 99 COVID-19 patients and 51 healthy controls, serum NINJ1 levels were significantly elevated in infected individuals and were further increased in non-survivors. Circulating NINJ1 levels correlated with inflammatory and immune dysregulation indicators, including C-reactive protein, procalcitonin, prothrombin time, neutrophil-to-lymphocyte ratio, and lymphocyte depletion. Receiver operating characteristic analysis demonstrated that serum NINJ1 exhibited significant predictive value for in-hospital mortality. Conclusions: Collectively, our findings identify NINJ1⁺ inflammatory monocytes as an activated immune state associated with the transition from protective innate defense to pathological inflammation, providing new insights into COVID-19 immunopathogenesis and highlighting NINJ1 as a promising biomarker candidate for risk stratification and therapeutic exploration. Full article

Subtropical bamboo forests are important carbon sinks, yet long-term regional assessments of their net ecosystem production (NEP) and associated factor contributions remain scarce. Here, using approximately 646 km² of mapped Moso bamboo (Phyllostachys pubescens) in Anji County, China, we generated a monthly NEP reconstruction on a 500 m output grid for 2003–2022 by integrating eddy covariance observations, meteorological data, and multi-source remote sensing products within an automated machine learning framework. Bamboo NEP showed weak overall spatial heterogeneity but followed a clear unimodal elevational pattern, with the highest carbon sequestration at mid-elevations (342–550 m). Regional carbon uptake peaked in summer and reached a minimum in winter, consistent with bamboo phenology. Annual mean NEP was 0.43 Tg C yr⁻¹ and increased significantly over the study period (3.35 Gg C yr⁻², p < 0.001), with 95.8% of bamboo pixels exhibiting upward trends. Negative modeled anomalies coincided with drought years, whereas the biennial growth cycle of Moso bamboo had little effect on annual NEP at the regional scale. SHapley Additive exPlanations (SHAP) shows that long-term NEP enhancement was dominated by canopy vegetation indices and exhibited a descriptive transition around 2013, when the leading control changed from solar radiation to vegetation conditions. Structural equation modeling (SEM) further showed statistical pathways in which meteorological variables were associated with modeled NEP partly through vegetation indicators. These findings reveal a sustained strengthening of the regional bamboo carbon sink and identify shifting controls on its long-term variability, providing a scientific basis for carbon sink management in subtropical bamboo forests under climate change. Full article

Background: Hepatocellular carcinoma (HCC) heterogeneity, particularly the presence of tumor cells co-expressing hepatocytic and cholangiocytic markers, contributes to therapeutic resistance and poor prognosis, yet its molecular correlates remain incompletely understood. This study aimed to characterize dual-phenotype HCC (DPHCC) and investigate the association and functional relevance of SPINT2 in tumor progression. Methods: We integrated multiplex immunofluorescence, CyTOF mass cytometry, single-cell RNA sequencing, and functional assays across clinical cohorts and cell lines. Results: Multiplex staining identified DPHCC in 22.89% of patients, correlating significantly with younger age, elevated AFP, and inferior recurrence-free and overall survival compared to non-DPHCC cases. Parallel scRNA-seq and CyTOF analyses showed that DPHCC-associated cells were enriched for stemness- and EMT-related features, with SPINT2 emerging as a top candidate gene in the transcriptomic analysis. Immunohistochemistry showed higher SPINT2 expression in DPHCC tissues, and high SPINT2 expression was associated with shorter overall survival in univariate Kaplan–Meier analysis and frequently co-localized with CK19. Functionally, SPINT2 modulation produced context-dependent changes in invasion, proliferation-related CCK-8 readouts, wound closure, sphere formation, and xenograft tumor growth in MHCC-97H and MHCC-LM3 cells. Collectively, these findings characterize DPHCC as a clinically relevant dual-lineage phenotypic state associated with aggressive tumor features and identify SPINT2 as a candidate molecule associated with this phenotype. Conclusions: SPINT2 is associated with the DPHCC-related state and aggressive tumor-cell phenotypes, but its mechanistic and clinical significance requires further validation. Full article

Background: Urban wastewater integrates chemical signals from human activities and provides a composite biochemical representation of the communities it serves. However, whether wastewater metabolomes exhibit stable spatial organization at the catchment scale remains insufficiently characterized. Methods: Untargeted LC–HRMS was applied to 56 influent wastewater samples collected from seven urban catchments over eight consecutive days to evaluate spatial structuring of the community metabolome. Results: A total of 3248 reproducible molecular features were detected. Permutational multivariate analysis of variance indicated that catchment identity explained 62% of total metabolomic variation (R² = 0.62, p < 0.001), while multivariate dispersion did not differ significantly among sites (p = 0.082). Within-catchment compositional distances were significantly lower than between-catchment distances (p < 0.001), and centroid separation exceeded internal dispersion (ratio = 2.55), indicating short-term stable, site-specific configurations in high-dimensional chemical space. Random Forest classification achieved 98% accuracy under strict spatial cross-validation and 98.2% under leave-one-day-out validation (p < 0.001). Classification performance remained high using annotated-only (98.2%), unannotated-only (98.2%), or pharmaceutical-excluded datasets (96.5%), demonstrating that spatial identity was encoded in a distributed manner across the metabolome rather than driven by a limited subset of compounds. Conclusions: These findings provide quantitative evidence that urban wastewater metabolomes exhibit short-term stable, reproducible catchment-level structure and establish a methodological foundation for system-level characterization of urban populations using untargeted metabolomics. Full article

Black soils are globally important for agricultural productivity, yet most studies of soil microbial communities are confined to the plow layer, leaving the deep regolith–bedrock interface largely unexplored. Here, we investigated bacterial diversity, community assembly, and co-occurrence networks along a 34-m regolith profile from the mollic epipedon to unweathered bedrock in the Songnen Plain, Northeast China. Bacterial alpha diversity exhibited a depth-dependent pattern with a secondary peak at 7.2–7.6 m, coinciding with buried organic carbon derived from paleolacustrine sedimentation. Community composition shifted significantly with depth, with Acinetobacter and Achromobacter enriching in deep layers as indicators of bio-weathering processes. Heterogeneous selection dominated community assembly, reinforced by strong dispersal limitation along the sedimentary gradient. Random forest and structural equation modeling identified depth as the primary driver, with pH, chemical weathering, and silt content mediating indirect effects. Network analysis revealed Chloroflexi as keystone taxa, with modules linked to methanogenic and nitrification functions in anaerobic deep strata. These findings demonstrate that sedimentary geochemical gradients and bacterial communities have co-evolved throughout the Black Soil Critical Zone, providing a mechanistic framework for whole-profile soil health management in one of the world’s most productive agricultural regions. Full article

Extracellular vesicles (EVs) have emerged as key mediators of intercellular communication, shuttling bioactive proteins, lipids, and nucleic acids between organs to maintain metabolic homeostasis. In this review, we provide an overview of recent advances in EV-mediated local and systemic communication across four interconnected metabolic diseases: diabetes, obesity, metabolic dysfunction-associated steatotic liver disease (MASLD), and sarcopenia, with a focus on the mechanistic roles of EVs in disease onset, adaptation, and progression. We highlight how EVs from the pancreas, adipose tissue, liver, and skeletal muscle propagate metabolic dysfunction across organs, and identify some shared cargo signatures, including miR-27a, miR-155, miR-146a-5p, miR-690, CXCL10, RBP4, ceramides, adipokine composition, and mitochondrial components, which may represent common pathogenic mechanisms. Current EV-based therapeutic strategies are discussed, and future efforts should prioritize the standardization of EV isolation and characterization to improve reproducibility, thereby facilitating clinical translation. Full article

The composition, richness, and diversity of rhizosphere fungal communities play significant roles in plant development in Chinese fir plantations. Understanding their structure and assembly, along with their relationship to soil physicochemical properties and root traits, is essential for maximizing the benefits of fungal symbionts for Chinese fir trees. Hence, fungal communities in two soil layers (0–20 cm and 20–40 cm) at four plantation developmental stages were analyzed using internal transcribed spacer rRNA gene sequencing. Soil physicochemical properties and root traits were examined to determine the main fungal community drivers. Our results revealed that fungal communities were significantly influenced by stand developmental stage, rhizosphere, and soil depth. Fungal biomass was highest at the young stand stage, whereas the α-diversity and evenness of the surface rhizosphere soil fungi remained stable across stages. With increasing stand age, the fungal community structure shifted from aggregated to dispersed. Co-occurrence network analysis demonstrated that stand development promoted network connectivity and modularity, with tighter local associations and distinct core functional consortia formed in the mature and over-mature stages. The proportion of positive links and positive cohesion increased along the stand developmental gradient, indicating a shift from competitive to cooperative interspecific interactions. Ascomycota and Basidiomycota consistently dominated soil fungal communities regardless of stand age, whereas Mortierellomycota and Chytridiomycota displayed sensitivity to stand development despite their low relative abundance. Soil physicochemical properties (total carbon, potassium, dissolved organic carbon, and phosphorus) were the primary drivers of rhizosphere fungal community dynamics and regulated fungal assembly by controlling soil resource availability. Additionally, the structural configuration of the fungal community was found to be intricately linked to root biomass and morphological traits. Full article

Elastic scattering angular distributions of ¹⁷Ne + ²⁸Si at $E_{\mathrm{lab}}=22.4$ MeV/u and ¹⁵O + ²⁸Si at $E_{\mathrm{lab}}=18.2$ MeV/u, well above the Coulomb barrier ($E_{\mathrm{cm}}/V_{\mathrm{B}}=9.7$ and $8.2$, respectively), have been measured at the HIRFL–RIBLL facility in Lanzhou. Time of flight–$\Delta E$ (TOF–$\Delta E$) beam identification, PPAC-based trajectory tracking, and a target–detector integrated DSSD telescope were employed for event-by-event reconstruction of scattering angles and particle identification. Detection efficiencies and solid angles were evaluated and corrected by means of Geant4 simulations. Theoretically, the real parts of the optical potentials were calculated within a double-folding model using the density-dependent BDM3Y1–Paris effective interaction, while the imaginary parts were taken as Woods–Saxon forms and adjusted by ${\chi }^2$ fits to the data using the SFRESCO code. ¹⁷Ne has a larger matter distribution than ¹⁵O. However, once mass scaling is removed, the real potential remains essentially unchanged, indicating the structural effects are not encoded in the real part. At the same time, a substantially deeper imaginary potential is required for the ¹⁷Ne + ²⁸Si system, pointing to stronger absorption and coupling effects. A further analysis in terms of the reduced distance of closest approach shows that both the strong-absorption distance $d_{\mathrm{S}}$ and the effective coupling range $\Delta d$ are larger for ¹⁷Ne than for ¹⁵O, whereas the Coulomb barrier height $V_{\mathrm{B}}$ follows the known systematics and is insensitive to structural differences. These findings provide reaction-based evidence that the more diffuse and weakly bound structure of ¹⁷Ne has a pronounced impact on the scattering dynamics on a light- to medium-mass target. Full article

We evaluate WRF 90 m wind speeds over Hami, China, using hourly observations from 12 towers during June 2016–May 2017. The study combines a tower-point seasonal hindcast, a four-model comparison at six WRF anchors, a bidirectional cross-farm evaluation, and monthly residual interpolation with 2016–2018 wind-power-density (WPD) scenarios. The March–May 2017 hindcast uses causal feature construction and training-period-only fitting on 26,367 matched tower-hour samples. Its two-stage ExtraTrees correction reduces central error relative to its power-law baseline but detects none of the 128 observed hours at or above 25 m⁻¹, revealing substantial loss of the high-wind tail. In a separate leave-one-WRF-anchor-out comparison, ET, DLinear, TCN, and CVAE use identical 48 h power-law wind histories at the six anchors; their unweighted anchor mean RMSE values span 3.521–3.540 m⁻¹ and all strongly underdetect 25 m⁻¹ h. In the cross-farm evaluation, shared-anchor observations were excluded from fitting: all models predict zero of 223 YW exceedance hours when trained with BLK observations, while the reverse direction gives low and variable POD values. For the monthly product, all towers at a held WRF coordinate were excluded from IDW donors. Across six anchors and 72 anchor-month comparisons, the unweighted mean RMSE decreases from 1.04 to 0.77 m⁻¹. The published power-2, fixed-density central WPD remains 726.7 W m⁻²; across 162 sensitivity cases varying IDW power, residual, cubic factor, density, and penalty weight, fixed-density and ISA means span 457.3–1102.5 and 411.0–988.5 W m⁻², respectively. Only 8.36% of product cells lie inside the six-anchor convex hull. Together, these analyses distinguish tower-point prediction, monthly interpolation, and regional WPD comparison. The maps support regional comparison and identify locations for follow-up measurement within the one-year tower record and six-anchor network. Full article

Incipient stator interturn short-circuit faults in permanent magnet synchronous motors produce only weak changes in the terminal currents, which limits the sensitivity of conventional amplitude- and unbalance-based indicators. This paper proposes a phase-wise diagnostic framework that combines multiscale sample entropy (MSE), topological data analysis (TDA), and a Gaussian mixture model (GMM). For each three-period current window, ten scale-dependent sample-entropy components and two persistent-entropy components are concatenated into a 12-dimensional feature vector. A separate GMM is trained for each phase using healthy data only. The resulting likelihood-based health scores are used for fault detection and faulty-phase localization, while physically defined score boundaries calibrated from measured short-circuit-current groups are used for severity assessment. Experiments on a 1.5 kW, 8-pole, 12-slot PMSM demonstrate class-wise recalls of 96.50–100% and an overall accuracy of 97.50% under the investigated operating conditions. The results show that the combined temporal and topological representation can reveal weak current changes that are difficult to distinguish using conventional terminal-current indicators. Full article

This study proposes a surrogate model, Graph-Structured Physics-Informed Deep Operator Network (GS-PI-DeepONet), to simulate two-dimensional hydrodynamics in a tidal river network. The model was coupled with Graph Convolutional Networks (GCNs) for spatial feature extraction and Long Short-Term Memory (LSTM) network for temporal prediction, with 2D shallow-water equations (2D SWEs) embedded as physical constraints. To handle complex river network topologies, a mapping mechanism was proposed to transform discrete irregular boundaries into differentiable neural network constraints. A dynamic weighting strategy was developed to improve model training efficiency. GS-PI-DeepONet was applied to a river network within the Pearl River Basin in Zhuhai. Trained on high-fidelity Delft3D data, it achieved precise flow field reconstruction and millisecond-level extrapolation predictions, outperforming traditional data-driven models. The model can be a valuable tool for real-time hydrodynamic simulations and flood management strategies in tidal river networks. Full article

Rice (Oryza sativa L.) is a staple food crop worldwide, and improving disease resistance is a core target in rice breeding. In this study, we employed CRISPR/Cas9 genome editing to modify the coding sequence (CDS) of two susceptibility genes, Bsr-d1 and Pi21, in the elite maintainer line Gengxiang B to enhance its blast resistance. We generated Bsr-d1/Pi21 double homozygous mutants via Agrobacterium-mediated genetic transformation. Quantitative RT-PCR revealed significantly suppressed transcript accumulation of both target genes in the edited lines compared with the wild type Gengxiang B. Upon inoculation with Magnaporthe oryzae, multiple defense-related marker genes were markedly upregulated in the double mutants. Phenotypic assays demonstrated significantly reduced disease severity for both leaf and panicle blast in the edited lines compared with the wild type. Importantly, no statistically detectable differences were found between the double mutants and wild-type plants for key agronomic or grain quality traits. Collectively, these results demonstrate that CRISPR/Cas9-mediated editing of susceptibility loci generates genetically stable blast-resistant rice germplasm without compromising agronomic traits or grain quality, providing valuable genetic resources for future rice varietal improvement. Full article

Soybean meal protein, a byproduct of soybean processing, has limited functional properties such as emulsifying performance, which restricts its application in foods. Given that high-temperature extrusion tends to cause excessive denaturation and irreversible aggregation, this study aimed to investigate the effects of relatively low extrusion temperatures (85–105 °C) on the structural and functional properties of soybean meal protein. The results showed that extrusion altered the molecular structure and functional characteristics of the protein. With increasing extrusion temperature, the β-sheet content increased while the α-helix content decreased in the secondary structure, and tertiary structural rearrangements occurred, with hydrophobic groups being exposed and subsequently buried. At 95 °C, the protein formed a relatively porous and loose microstructure and exhibited the strongest surface hydrophobicity, water-holding capacity, oil-holding capacity, and emulsifying properties; at 100 °C and above, excessive aggregation occurred, pore structure collapsed, and functional properties declined. Meanwhile, extrusion generally reduced protein solubility. Therefore, 95 °C is identified as the optimal extrusion temperature under the conditions of this study. In addition, this study reveals the correlation between structural reconstruction and functional changes of soybean meal protein, providing a theoretical basis for its high-value utilization and application in the food industry. Full article

Chinese yam possesses anti-type 2 diabetes mellitus (T2DM) potential. However, existing research has focused on its polysaccharides rather than its abundant peptide components. Therefore, this study integrated peptidomics with network pharmacology and molecular docking to explore the potential anti-T2DM mechanisms of Chinese yam peptides. Firstly, this study revealed that crude peptides extracted from Chinese yam possessed a potential hypoglycemic activity, with an IC₅₀ of 568.87 μg/mL against α-glucosidase. Secondly, peptidomics identified 558 peptides with the sequences ranging from 3 to 25 residues. Thirdly, network pharmacology was conducted on 15 candidate peptides selected through bioactivity prediction and safety evaluation. These peptides shared 466 common targets with T2DM, with seven core targets identified through topological network analysis: SRC, EGFR, PTPN11, PIK3R1, ESR1, STAT3, and PIK3CA. Enrichment analysis revealed that these targets were significantly associated with PI3K-Akt and MAPK signaling pathways. Fourthly, molecular docking confirmed the strong binding affinities between the 15 bioactive peptides and seven core targets, particularly the high-affinity binding of peptides SIDLYENRL and RAPDDLDTRL to PIK3CA. Collectively, these findings demonstrate that Chinese yam peptides possess potential hypoglycemic activity and may ameliorate T2DM through the regulation of insulin signaling via PI3K-Akt activation and the modulation of inflammation via the MAPK pathway. Full article

The variation in thermal stratifications significantly alter the distribution of the wind load on buildings. In this study, large eddy simulation (LES) was adopted to investigate this influence on an isolated cubic building. The thermally stratified turbulent inflow for LES was synthesized by a modified generation method, which combines equilibrium boundary conditions with empirical stability functions and integrates them into the Fluent inherent vortex method. The effectiveness of the present method was verified by comparison with corresponding wind tunnel test data under neutral stratification. The simulated wind load around an isolated cubic building was then compared across three thermal stratification conditions, including neutral, stable and unstable stratification. Compared with the neutral stratification, variations in temperature result in variations in the position and morphology of the horseshoe vortex location at the windward side and separation vortex at the top under stable and unstable stratifications, changing the distribution characteristics of wind pressure in those areas. On the leeward side, the wind pressure and its non-Gaussian characteristics under stable and unstable stratifications are enhanced due the variation in temperature. The extreme wind pressure coefficient at the bottom region of the leeward surfaces under the stable and unstable stratification increases by 1.38- and 1.50-fold, respectively. Full article