Search Results (410)

A formal framework of bioprocesses enables accurate prediction of reaction outcomes, thereby optimizing resource allocation and reducing production costs. This study aimed to establish an approximate stoichiometric equation and determine the bioenergetics growth parameters of the pink oyster mushroom (Pleurotus djamor) using a “black box” modeling approach. A commercial strain was cultivated in polypropylene bags at 28 °C and 75% relative humidity. The harvested mushroom biomass was dried and analyzed for C, H, and N content, with O determined by difference. The resulting empirical formulas were CH_1.33O_0.36N_0.02 for the dry wheat straw substrate and CH_1.81O_0.41N_0.09 for the fungal biomass. The bioprocess exhibited a primordia initiation period of 20.5 days, a total harvest window of 50.0 days, a maximum biological efficiency of 16.77%, a model yield (Y) of 0.90%, and a productivity of 20.5 g/100 g substrate. In conclusion, this biotechnological framework provides a robust predictive tool for industrial scaling, enabling mass and energy balance optimization in real time without reliance on costly intracellular measurements. Thus, it establishes a reliable and sustainable pathway to convert low-cost agricultural residues into high-value bioproducts, supporting the goals of a circular economy. Full article

Soil acidification threatens agroecosystems, yet the coupled, soil-specific proton-buffering mechanisms in permanent-charge soils (PCSs) and variable-charge soils (VCSs) remain insufficiently quantified. This study systematically investigated surface cation exchange, vacant site H⁺ sorption, and mineral dissolution, using batch and kinetic incubation experiments. Results showed that H⁺ buffering in PCSs was dominated by rapid, stoichiometric surface ion exchange, whereas approximately 42% of the total exchangeable acidity increment in VCSs originated from specific H⁺ sorption on vacant, high-affinity surface sites. VCSs exhibited ~10-fold-higher Langmuir proton sorption affinity and Temkin acid-buffering capacity than PCSs, driven by their more homogeneous, pH-dependent surface properties favoring inner-sphere coordination. Base cation release followed Ca²⁺ ≫ Mg²⁺ ≫ Na⁺ ≈ K⁺ across all soils; VCSs showed a twofold-higher Mg²⁺ pseudo-second-order rate constant and a strong Mg²⁺-Mn²⁺ positive correlation (R² > 0.804, p < 0.0001), exposing them to dual risks of Mn phytotoxicity and Mg deficiency during acidification. The well-fitted parabolic diffusion model for Al³⁺ and Mn²⁺ release further indicated prolonged, diffusion-limited metal toxicity risk in VCSs. A critical soil organic carbon (SOC) threshold of 8.1 g kg⁻¹ was identified, exceeding this value effectively retarded acidification via enhanced cation exchange capacity (CEC) and base retention. These findings provided a mechanistic framework for developing soil-specific strategies to manage and mitigate agricultural soil acidification. Full article

Accessible molecular diagnostics is fundamental to effective healthcare. While most current point-of-care devices detect only the presence of a molecular biomarker(s), biomarker quantification can be equally important for decision-making on disease treatment and containment. Here, we present a diagnostic platform that enables the equipment-free quantification of molecular biomarkers with the simplicity of a binary (yes/no) readout. This capability is achieved by integrating a stoichiometric quantitative approach with widely available and easy-to-use lateral flow dipsticks. To implement the approach, we engineer negative cooperativity into target–probe binding interactions for oligonucleotide targets as a model system. The resulting threshold-based semi-quantitative assay with lateral flow dipsticks quantifies targets in the low-nanomolar range and operates reliably in complex biological backgrounds. A key advantage of this platform is its potential adaptability to new and emerging targets: repurposing will require only reagent redesign, without the need for additional fabrication. Full article

The spread of Bursaphelenchus xylophilus has caused a critical shortage of traditional Poria cocos cultivation materials, making bag-based substrates an urgent alternative. Yet, how substrate stoichiometry shapes nutritional quality remains unclear. Using non-targeted metabolomics combined with redundancy analysis (RDA) and weighted gene co-expression network analysis (WGCNA), we profiled P. cocos cultivated on four substrates: healthy pine logs, pine wilt wood bags, oak bags, and pine needle/branch bags. Bag-cultivated P. cocos showed significantly elevated total amino acids, poria cocos acid, and total triterpenoids, with pine wilt wood bags (P1) performing best overall. Nitrogen, phosphorus, and the N/P ratio independently drove metabolomic variation (pairwise overlap < 5%). Nitrogen-line hub metabolites were negatively correlated with amino acid content, suggesting that suppressed lipid metabolism may free carbon skeletons for the accumulation of nitrogenous nutrients. Phosphorus-line hub metabolites were positively associated with polysaccharide indices, whereas the N/P ratio in line lipid amides showed strong negative correlations with polysaccharides under phosphorus limitation. These correlational patterns are consistent with a stoichiometric resource allocation model, although direct validation through controlled-element experiments is required. These findings provide quantitative guidance for optimizing bag-substrate formulations in P. cocos cultivation. Full article

Background: In liver transplantation, maintaining donor organ viability is a critical factor determining transplant outcomes. The aim of this study was to evaluate liver metabolic activity under ex vivo perfusion in the presence of magnetite magnetic nanoparticles using mathematical modeling. Methods: Ex vivo liver perfusion was performed with nanoparticles added to the perfusate; the concentration of nanoparticles in the inflowing and outflowing perfusate was determined by mass spectrometry. A stoichiometric model of hepatic metabolic fluxes was constructed, and the distribution of energy resources was assessed using the Zipf–Pareto law and its linear approximation, the Zipf–Pareto–Mandelbrot distribution. Results: It was shown that nanoparticle uptake by the liver increased from 26.5% to 54.4% over the course of perfusion. The introduction of magnetic nanocomposites altered metabolic fluxes, including glycolysis, the respiratory chain, and oxygen exchange across the surface, leading to redistribution of energy resources within liver cells. Zipf–Pareto analysis showed that energy was optimally distributed among all metabolic fluxes both in the control condition and in the presence of nanoparticles. Conclusions: Magnetic nanoparticles alter liver metabolic activity, but the functional state of the organ remains intact. Full article

Green hydrogen is a key energy carrier in Power-to-Liquid (PtL) pathways for the production of sustainable synthetic fuels, contributing to the decarbonization of the industrial and transport sectors. However, the intermittent nature of renewable energy sources and the variable hydrogen requirements needed to maintain the appropriate stoichiometric ratio for synthesis processes necessitate regulating hydrogen production according to process demand, rather than maximizing its generation. This article proposes an intelligent control strategy for alkaline water electrolysis, in which the hydrogen production target is determined from the stoichiometric requirements of synthetic methanol production, based on available carbon dioxide. ANN models were developed using the experimental data, incorporating both classical and conformable activation functions in the hidden layer. Based on the selected models, the ANNi was formulated, and PSO and GA were used to determine the required feed current according to hydrogen demand. The proposed methodology was evaluated under a dynamic hydrogen-demand profile derived from the stoichiometric requirements of methanol synthesis. The results show that the proposed controllers closely track changes in hydrogen demand. After each change in the setpoint, the H₂/CO₂ ratio returned to a $\pm 2\%$ band around the stoichiometric setpoint in approximately 0.98 s for ICANNi-PSO and 0.96 s for ICANNi-GA. Furthermore, some conformable activation functions achieved performance comparable to that of classical activation functions while using fewer neurons in the hidden layer. Both optimization algorithms provided comparable tracking performance under the evaluated conditions. Full article

Agricultural intensification with synthetic fertilisers has systematically disrupted soil organic carbon (SOC), influenced rhizosphere networks, and affected human health via the soil–human microbial continuum. Plant Growth-Promoting Microorganisms (PGPMs) can restore biogeochemical cycles; however, field performance varies due to spatial stoichiometric variation. In order to visualise the problem and provide a potential solution, we use global soil carbon-to-nitrogen (C/N) ratio stratification over three depth profiles (0–5, 5–15, and 15–30 cm) to create a potential spatially explicit framework for site-specific PGPM application. In comparison to contemporary models that attribute stable soil organic matter creation mostly to microbial necromass buildup as mineral-associated organic matter (MAOM) via the microbial carbon pump, we assess diazotrophic nitrogen fixation, phosphate solubilisation, and glomalin-mediated aggregation. According to stoichiometric analysis, low C/N ratios (<10:1) increase organic matter mineralisation via priming effects, resulting in clay compaction and sandy soil desiccation, while wide ratios (>30:1) cause microbial nitrogen immobilisation (“nitrogen depression”). To mitigate these limitations, we proposed depth-stratified inoculation, applying chemotactic taxa (Variovorax paradoxus) at 15–30 cm in carbon-depleted subsoils; co-inoculating diazotrophs and arbuscular mycorrhizae (Rhizophagus irregularis) at 5–15 cm for stoichiometric balance and phosphorus acquisition and deploying exopolysaccharide-producing and 1-aminocyclopropane-1-carboxylate (ACC) deaminase-active taxa (Pseudomonas putida, Funneliformis mosseae) at 0–5 cm for erosion. In conclusion, in order to maximise fertiliser use efficiency, improve structural stability, and protect metabolic health within the interdisciplinary One Health framework, we assess the shift toward trait-based, multi-kingdom Synthetic Microbial Communities (SynComs), assembled via genomic metabolic reconstructions and machine learning. We explicitly acknowledge methodological limits in existing field applications, such as substantial spatial variability, equipment constraints, and biotic competition, putting scientific validity ahead of generalised efficacy. Full article

Electrochemical conversion of carbon dioxide (CO₂) to ethanol offers a potential route for integrating carbon utilization with low-carbon electricity; however, its environmental performance is governed by the complete process system rather than by catalytic selectivity alone. This study presents a detailed attributional cradle-to-gate life cycle assessment of anion-exchange-membrane (AEM) and bipolar-membrane (BPM) electrolyzer systems using a functional unit of 1 kg of ethanol at the plant gate. The foreground inventory combines stoichiometric balances, peer-reviewed electrochemical evidence, process-energy estimates, and transparent engineering assumptions, while background processes are represented using ecoinvent 3.7.1. Climate-change impacts are evaluated with the IPCC 2021 100-year global warming potential method. The modeled AEM and BPM systems require 23.32 and 27.92 kWh of electricity per kilogram of ethanol, respectively. Wind-powered operation yields the lowest reported impacts, at 0.318 kg CO₂-eq kg⁻¹ ethanol for AEM and 0.442 kg CO₂-eq kg⁻¹ for BPM. Photovoltaic scenarios yield 1.812 and 2.231 kg CO₂-eq kg⁻¹, whereas the Austrian-grid scenarios yield 1.349 and 4.686 kg CO₂-eq kg⁻¹, respectively. Electricity supply is the dominant environmental driver, while separation heat, carbon utilization, component lifetime, and oxygen co-product treatment remain important secondary parameters. The BPM Austrian-grid result is disproportionately high relative to the 19.7% increase in modeled electricity demand and therefore requires exchange-level verification before it can be interpreted as a physical membrane effect. Overall, environmentally credible CO₂-to-ethanol deployment requires low-carbon electricity, reduced cell voltage, efficient carbon management, concentrated product streams, durable components, and transparent co-product accounting. Full article

Permafrost peatlands in high-altitude regions store substantial amounts of organic carbon, yet the biogeochemical consequences of thermokarst collapse remain poorly understood. Using a space-for-time substitution approach, we selected four habitats representing a thermokarst development sequence in the Altai Mountains peatlands—slightly collapsed peat mounds (P1), severely collapsed peat mounds (P2), thawed herbaceous peat (PB1), and thermokarst ponds (PB2)—and conducted in situ greenhouse gas flux monitoring, soil physicochemical analysis, enzyme activity assays, and structural equation modeling. We found that thermokarst development fundamentally altered the greenhouse gas source–sink balance through three interconnected mechanisms. First, CO₂ fluxes shifted from net emission in P1 (684.1 mg m⁻² h⁻¹) to net uptake in PB2 (−25.6 mg m⁻² h⁻¹), driven primarily by the oxidative loss of mineral-associated organic carbon in the 40–60 cm layer (71.3% loss), whereas lateral dissolved organic carbon export accounted for only 12.3% of total carbon loss. Second, CH₄ fluxes in PB2 (3.8 ± 0.7 mg m⁻² h⁻¹) reached approximately 43% of the theoretical maximum, with this suppression associated with phosphorus limitation (total phosphorus < 0.05 g kg⁻¹) and a marked reduction in alkaline phosphatase activity. Third, N₂O uptake increased along the thaw sequence to −28.6 μg m⁻² h⁻¹ in PB2, with the 40–80 cm layer contributing 42% more than the surface layer. This increase in N₂O uptake occurred when the soil C/N ratio exceeded 300, a threshold that reflects the substantial stoichiometric imbalance between carbon and nitrogen following thermokarst development. These findings demonstrate that the transition from peat mounds to thermokarst ponds alters the net greenhouse gas source–sink balance through changes in MAOC stability, phosphorus availability, and carbon-to-nitrogen stoichiometry. Our results provide empirical constraints for evaluating carbon-climate feedbacks in cold-region peatlands. Full article

This paper presents a hybrid physics–AI framework for real-time emission monitoring in industrial boiler systems within an IIoT-enabled Industry 4.0 environment. The proposed framework integrates physics-based emission estimation with AI-based anomaly detection within a unified operational technology and information technology (OT–IT) architecture to support continuous environmental monitoring. Process data, including fuel oil consumption, oxygen concentration, temperature, and pressure, are acquired from an industrial boiler through a Siemens programmable logic controller (PLC) using an Open Platform Communications Unified Architecture (OPC UA) communication layer. The acquired measurements are processed at the edge analytics level to estimate the emission rates of carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter (PM) using stoichiometric combustion models based on fuel composition and flue gas characteristics. An autoencoder-based anomaly detection model is employed to identify abnormal operating conditions by monitoring the reconstruction error against a predefined threshold. The framework is validated using a PLC-based quasi-real-time prototype that replays one year of historical industrial boiler operating data. The emission estimation results show close agreement with reference engineering calculations, with relative errors below 0.1% across the evaluated operating conditions. The anomaly detection model achieved an F1-score of 96.14% and an AUC of 0.981. An edge monitoring dashboard provides real-time visualization of process variables, estimated emissions, and alarm status, while cloud connectivity supports remote monitoring and long-term data analytics. Overall, the proposed framework demonstrates how existing industrial process data can be utilized to transform conventional offline emission estimation into a continuous OT–IT monitoring service for legacy industrial environments. Full article

This study investigates the sorption, structural, and morphological properties of an interpolymer system (IPS) based on Amberlite IR120 (H⁺) and KU-2-8 (H⁺) cation exchangers with acidic sulfonic groups (−SO₃H), applied for the selective sorption of dysprosium (Dy³⁺), neodymium (Nd³⁺), and samarium (Sm³⁺) ions from aqueous solutions. The sorption activity was evaluated for seven systems with molar ratios ranging from 6:0 to 0:6 over a contact time of up to 48 h within a pH range of 2.0 to 5.0. The interpolymer pair with a molar ratio of 5:1 demonstrated the highest sorption efficiency at pH 5.0, yielding extraction degrees of 61.8% for Dy³⁺, 62.0% for Nd³⁺, and 64.4% for Sm³⁺. Equilibrium data were accurately described by the Langmuir isotherm model (R² > 0.974), indicating a dominant monolayer chemisorption mechanism. The maximum monolayer adsorption capacities (q_m) followed the order Dy(III) (189.59 ± 31.52 mg/g) > Sm(III) (162.27 ± 52.38 mg/g) > Nd(III) (139.90 ± 35.40 mg/g). The selectivity toward dysprosium was supported by distribution coefficients (Kd) and separation coefficients (β_Dy/Nd = 1.557 and β_Dy/Sm = 1.757 for the 6:0 system). FTIR analysis confirmed the direct coordination of lanthanide ions by sulfonic groups, as evidenced by the shifts in the νas(S=O) bands. SEM-EDX characterization revealed distinct post-sorption morphological changes (surface cracking and flaking) and confirmed significant REE accumulation on the resins (up to 4.04 wt.%) coupled with a stoichiometric decrease in sulfur content, validating the ion-exchange mechanism. These findings provide a deeper insight into the remote conformational effects governing interpolymer interactions and offer a highly promising approach for the selective recovery of REEs in hydrometallurgy. Full article

Soil microbial carbon use efficiency (CUE) and nitrogen use efficiency (NUE) are fundamental parameters governing organic matter turnover in terrestrial ecosystems, yet how forest type-driven variation in litter quality propagates through the litter–soil–microbe continuum to regulate these efficiencies remains poorly resolved. Across three forest types in the Funiu Mountains, central China—a Larix gmelinii (LG) plantation, a Quercus aliena var. acuteserrata (QA) secondary forest, and a mixed Quercus aliena var. acutiserrata and Pinus armandii (QP) forest—we quantified litter chemistry, soil physicochemical properties, microbial biomass, extracellular enzyme activities, and microbial nutrient use efficiencies (MUE: NUE, and phosphorus use efficiency, PUE) derived from a modified saturation kinetics model. Principal coordinate analysis revealed significant multivariate differentiation among forest types across litter, soil, microbial biomass, and enzyme modules (Adonis R² = 0.198–0.427; all p < 0.05). Compared with LG and QA, QP exhibited a pronounced stoichiometric imbalance: it supported the highest litter organic carbon and total nitrogen, the lowest lignin-to-cellulose ratio, the largest soil C and N pools (SOC and STN), and the greatest microbial biomass carbon (MBC). However, despite this resource-rich environment, microbial biomass C:N:P ratios exhibited constrained variation, while soil C:P (SCP) and N:P ratios (SNP) in QP reached extreme values (112.3 and 7.25, respectively), generating severe stoichiometric imbalance. Vector analysis indicated that all forests were under relative nitrogen limitation (vector angle < 45°), with QP showing the strongest limitation (41.6 ± 0.4°). Critically, QP exhibited the highest NUE (0.47 ± 0.03) but the lowest CUE (0.95 ± 0.01), and CUE and NUE were nearly perfectly negatively correlated across all sites (R = −0.98, p < 0.001). Random forest analysis identified extracellular enzyme stoichiometry as the dominant proximate predictor of MUE. Partial least squares structural equation modeling (GOF = 0.673–0.674; R² = 0.592–0.603) revealed that litter and soil properties had no significant direct effects on CUE or NUE; instead, soil nutrients exerted strong indirect association through a cascade—soil → microbial biomass → enzyme activity—with opposite total effects on CUE (−0.731, p < 0.001) versus NUE (+0.755, p < 0.001). These findings reveal that the same soil nutrient enrichment that accompanies mixed-species afforestation drives divergent microbial metabolic responses—suppressing CUE while promoting NUE—through a shared cascading structure, with implications for predicting soil carbon and nutrient retention under shifting forest compositions. Full article

Coastal saline–alkaline land has considerable potential for soil carbon sequestration, but how different land-use types affect microbial resource limitation and carbon-use efficiency (CUE) in coastal saline–alkaline soils remains unclear. Four representative land-use types, namely bare land (BL), wetland (WL), grassland (GL), and forest land (FL), were investigated in the coastal saline–alkaline soils of the Yellow River Delta. Soil physicochemical properties, microbial biomass, and extracellular enzyme activities were measured, and ecoenzymatic stoichiometry, microbial resource limitation, and CUE were subsequently calculated. Compared with BL, vegetated land-use types decreased electrical conductivity by 52.1–95.8%, while soil water content, soil nutrient indicators, and microbial biomass indicators increased by 47.1–77.5%, 2.6–136.8%, and 2.2–274.4%, respectively. WL was mainly phosphorus-limited, whereas BL, GL, and FL were primarily nitrogen-limited. Despite relatively high soil organic carbon and nutrient availability, GL showed the strongest N limitation and was the only land-use type showing C limitation. Model-estimated CUE ranged from 0.544 to 0.579 and followed the order FL > BL > WL > GL. Random forest analysis showed that soil physicochemical properties contributed most to CUE variation (42.9%). Structural equation modeling further indicated that soil physicochemical properties were indirectly associated with CUE, mainly through stoichiometric characteristics and microbial resource limitation, showing positive and negative associations, respectively. These findings provide microbial evidence for optimizing land-use patterns, vegetation restoration, and carbon-oriented ecological restoration in coastal saline–alkaline land. Full article

Warming profoundly influences soil respiration in terrestrial ecosystems, thereby altering global carbon cycling. Understanding the trends and drivers of soil respiration changes in forest ecosystems under warming is essential for assessing regional carbon budgets and ecosystem carbon sink/source dynamics. In this study, a one-year warming experiment was conducted using open-top chambers in a Taxodium hybrid (Zhongshanshan) ecosystem in the northern Jiangsu coastal area, China. Treatments included control (CK) and warming (W), focusing on soil respiration components (soil respiration, Rs; heterotrophic respiration, Rh; autotrophic respiration, Ra) and associated soil hydrothermal and nutrient factors. Results showed that both warming and season significantly affected Rs, Rh, and Ra, all exhibiting a unimodal seasonal pattern peaking in summer. Warming increased winter Ra by 117.39% (p < 0.001). Bivariate models (temperature and moisture) explained more variation in respiration (R² = 0.720–0.893) than univariate models. Correlation analysis indicated that under control conditions, Rs components were significantly positively correlated with microbial biomass carbon (MBC), ammonium nitrogen (NH₄⁺-N), and available phosphorus (AP). After warming, these positive correlations with MBC and AP persisted; however, negative correlations emerged with soil organic carbon (SOC) and its stoichiometric ratios (C:N, C:P). Additionally, Ra showed negative correlations with easily oxidizable carbon (EOC), total nitrogen (TN), and N:P. Overall, these findings suggest that climate warming may enhance soil respiration in the Taxodium hybrid (Zhongshanshan) ecosystem by altering soil thermal-hydrological and nutrient factors, although further validation is needed. Full article

Investigating the adaptive mechanisms of different plant growth forms to flooding gradients is essential for formulating scientific vegetation allocation models to support ecological restoration in aquatic–terrestrial ecotones and mitigate ecological risks associated with summer flooding. This study focused on 38 adaptable species under three flooding gradients in the Taihu Lake aquatic–terrestrial ecotone. We systematically measured leaf morphological traits, photosynthetic physiological parameters, and stoichiometric characteristics. Employing analysis of variance, correlation networks, and principal component analysis, we elucidated how flooding environments shape leaf functional trait patterns of woody and herbaceous plants. The results indicated the following. (1) With increasing flooding stress, herbaceous plants increase the leaf area (LA) and leaf dry weight (LDW), whereas woody plants decrease them, indicating that herbaceous plants demonstrate stronger adaptability than woody plants. (2) Woody plants constructed a leaf functional trait network centered on stomatal conductance (G_s), adopting a conservative resource-use strategy. In contrast, herbaceous plants formed a network centered on leaf nitrogen content (N_mass), employing a rapid resource acquisition strategy to adapt to the ecotone environment. (3) The synergistic changes in leaf traits of different growth forms were affected by flooding in distinct ways. Integrating the leaf economics spectrum and adaptive evaluation values for each species can further our understanding of plant adaptation strategies in different flooding environments and guide species selection and configuration for aquatic–terrestrial ecotone restoration. Full article