Search Results (51)

Fungi have emerged as versatile biotechnological platforms for addressing environmental challenges with potential co-benefits for human health. Among them, Pleurotus ostreatus stands out for its ligninolytic enzyme systems (notably laccases), capacity to valorize lignocellulosic residues, and ability to form functional mycelial materials. We conducted an evidence-mapped review, based on a bibliometric analysis of the Scopus corpus (2001–2025; 2085 records), to characterize research fronts and practical opportunities in environmental remediation and sustainable bioprocesses involving P. ostreatus. The mapped literature shows sustained growth and global engagement, with prominent themes in: (a) oxidative transformation of phenolic compounds, dyes and polycyclic aromatic hydrocarbons; (b) biodegradation/bioconversion of agro-industrial residues into value-added products; and (c) development of bio-based materials and processes aligned with the circular bioeconomy. We synthesize how these strands translate to real-world contexts, reducing contaminant loads, closing nutrient loops, and enabling low-cost processes that may indirectly reduce exposure-related risks. Key translational gaps persist: standardization of environmental endpoints, scale-up from laboratory to field, performance in complex matrices, life-cycle impacts and cost, ecotoxicological safety, and long-term monitoring. A practical agenda was proposed that prioritizes field-scale demonstrations with harmonized protocols, integration of life-cycle assessment and cost metrics, data sharing, and One Health frameworks linking environmental gains with plausible health co-benefits. In conclusion, P. ostreatus is a tractable platform organism for sustainable remediation and bio-manufacturing. This evidence map clarifies where the field is mature and where focused effort can accelerate the impact of future research. Full article

The growing production of strawberry-based foods generates large quantities of pomace, a phenolic-rich by-product with high valorization potential. This study aimed to optimize ultrasound-assisted extraction (UAE) of strawberry pomace and to evaluate the bioactivity of the resulting extracts. The greenness assessment using the AGREEprep metric yielded a score of 0.68/1, confirming the environmental friendliness of the process. Under the optimized UAE conditions (20 min, 50 °C, solid-to-liquid ratio 1:20 g/mL), the extract exhibited the highest total phenolic (16.49 mg GAE/g) and flavonoid contents (2.10 mg RE/g). The optimized extract showed strong antioxidant activity, with DPPH, ABTS, CUPRAC, and FRAP values of 32.70, 46.76, 57.29, and 38.90 mg TE/g, respectively. Enzyme inhibition was particularly pronounced against tyrosinase (55.45 mg KAE/g), while moderate inhibition of acetylcholinesterase and butyrylcholinesterase was also observed. Artificial neural network (ANN) modeling demonstrated excellent predictive performance (R² > 0.99) and enabled effective optimization of extraction parameters. These findings confirm UAE as an efficient and sustainable approach for strawberry pomace valorization and highlight ANN-based optimization as a robust tool for developing multifunctional bioactive extracts for food, nutraceutical, and pharmaceutical applications. Full article

Evidence for diet-driven immunomodulation remains limited in terms of practical tools. This pilot study prospectively evaluated the dietary POLA index in 51 women aged 25–45 years and living in Kraków, Poland. At baseline (2022), 7-day dietary intake and physical activity were recorded; stool samples were analyzed for gut microbiota composition; short-chain fatty acids were quantified using high-performance liquid chromatography; and fecal secretory IgA (sIgA), human β-defensin-2 (HBD-2), and calprotectin levels were measured by the enzyme-linked immuno-sorbent assay. In June 2023, post-baseline incidence of COVID-19 and influenza was self-reported. Participants were categorized into a group with beneficial immunomodulation (BIM, POLA score ≤ 5) and a group with unbeneficial/highly unbeneficial immunomodulation (UBIM + HUBIM, POLA score > 5). The incidence of COVID-19 or influenza was 7.7% (1/13) in the BIM group vs. 36.8% (14/38) in the UBIM + HUBIM group. After adjusting for age and smoking, the UBIM + HUBIM group had higher odds of infection compared with the BIM group (adjusted OR = 6.53; 95% CI: 1.02–129.85), corresponding to a higher absolute risk of 47.9% (95% CI 26.1–70.6) versus 12.3% (95% CI 1.4–58.1). The BIM group more often met the fiber and micronutrient adequacy targets and showed a higher proportion of sIgA levels within the reference range (92.3% vs. 60.5%), along with lower fecal succinic acid concentrations (median 3.27 mg/g vs. 4.32 mg/g). In this cohort, a favorable POLA score was associated with lower self-reported COVID-19 or influenza incidence and an sIgA profile suggestive of intestinal immune homeostasis. As this pilot study is underpowered, findings should be interpreted as exploratory and hypothesis-generating. Nonetheless, results support the POLA index as a practical diet-quality metric with potential immunomodulatory relevance. Full article

To investigate the effects of supplementing the diet with Caulerpa lentillifera on the growth performance, antioxidant capacity, and intestinal microbiota of Litopenaeus vannamei, a total number of 600 healthy shrimp, each having an average body weight of 2.45 ± 0.12 g, were allocated randomly into five experimental groups. These groups comprised a control group receiving a basal diet (Ctrl) and four treatment groups receiving the basal diet supplemented with varying concentrations of dried C. lentillifera powder: 2.5% (CL1), 5% (CL2), 7.5% (CL3), and 10% (CL4). Each group consisted of four replicates, with 30 shrimp per replicate. The experimental duration was 56 days. The findings demonstrated that supplementing the diet with 5–7.5% C. lentillifera enhanced growth performance and significantly increased the crude protein content in whole shrimp (p < 0.05). Based on the feed conversion ratio (FCR) and protein efficiency ratio (PER) metrics, the optimal inculusion range of C. lentillifera in L. vannamei feed was determined to be 5.25–7.15%. Simultaneously, there was a significant increase in the activities of total superoxide dismutase (T-SOD), glutathione peroxidase (GPx), and peroxidase (POD) enzymes in the hepatopancreas, accompanied by a substantial reduction in malondialdehyde (MDA) levels (p < 0.05). Dietary supplementation with 5–7.5% C. lentillifera induced a numerical elevation of the relative expression levels of antioxidant and protein synthesis genes, although no statistically significant differences were detected among all groups (p > 0.05). Analyses of intestinal microbiota sequencing revealed that the addition of 5–7.5% C. lentillifera improved the intestinal microbiota’s composition and structural characteristics with a focus on metabolic pathways. In conclusion, the inclusion of dietary C. lentillifera positively influenced growth performance, antioxidant capacity, and the intestinal microbiota of L. vannamei. However, excessively high-dose dietary levels may have adverse effects on shrimp; thus, a dietary inclusion level of 5.25–7.15% C. lentillifera is recommended. Full article

Enzyme kinetics is fundamental across diverse fields—from enzymology and medicine to biocatalysis and metabolic engineering. Analyses of enzyme kinetics provide insights into catalytic rates, substrate affinities, inhibition patterns, productivities and mechanistic pathways, which are critical for areas such as drug development, industrial biocatalysis and mechanistic enzymology. However, each research field emphasizes different types of kinetic parameters, leading to challenges in establishing a common ground for understanding and interpreting enzyme properties. This review covers interpretation of enzyme kinetic parameters under three main categories—steady-state, transient-state and performance metrics—in a descriptive way and discusses their relevance with respect to different scientific and applied fields that investigate and utilize enzymes. By comparatively defining key kinetic and thermodynamic parameters, the review aims to help researchers interpret and report enzyme behavior more effectively, bridging gaps across interdisciplinary fields. Full article

Low temperature combined with fluctuating irradiance frequently co-occurs and suppresses photosynthesis, with irreversible injury to photosystem I (PSI) recognized as a key constraint on growth and yield. To test whether exogenous hydrogen sulfide (H₂S) mitigates this “cold–fluctuating light” stress in mulberry, we established six treatment combinations (room temperature controls, sodium hydrosulfide, and hypotaurine, each with or without low temperature plus fluctuating light). We quantified PSI/PSII photochemical properties, gas exchange, reactive oxygen species (ROS), and antioxidant enzyme activities. Under cold with fluctuating light, PSI was strongly inhibited: Y_NA increased, whereas Y_I and ΔI/I_o decreased, and the P700 re-reduction half-time (t½) was prolonged (ANOVA, Tukey’s HSD, p < 0.05), indicating pronounced acceptor-side over-reduction and impaired electron transport. PSII performance also declined (lower F_v/F_m and PI_ABS, higher ΔV_J; p < 0.05). NaHS pretreatment significantly alleviated these effects relative to the stressed control: PSI/PSII metrics partly recovered, net photosynthetic rate (P_n) and water-use efficiency (WUE) increased, H₂O₂ and MDA decreased, and SOD/POD/CAT activities rose (p < 0.05). Notably, NPQ_high correlated negatively with Y_NA (Pearson r < 0, p < 0.001), consistent with the notion that enhanced energy dissipation relieves PSI acceptor-side limitation. We propose that exogenous H₂S stabilizes electron transport and supports carbon assimilation via a dual strategy—faster engagement of energy dissipation and activation of antioxidant defenses—highlighting its potential utility for managing stress in fruit crops under erratic early-season weather. Full article

Under the dual carbon goals, microgrids face significant challenges in managing multi-energy flow coupling and maintaining operational robustness with high renewable energy penetration. This paper proposes a novel dynamic pressure-aware spatiotemporal optimization dispatch strategy. The strategy is centered on intelligent energy storage and enables proactive energy allocation for critical pressure moments. We designed and validated the strategy under an ideal benchmark scenario with perfect foresight of the operational cycle. This approach demonstrates its maximum potential for spatiotemporal coordination. On this basis, we propose a Multi-Objective Self-Adaptive Hybrid Enzyme Optimization (MOSHEO) algorithm. The algorithm introduces segmented perturbation initialization, nonlinear search mechanisms, and multi-source fusion strategies. These enhancements improve the algorithm’s global exploration and convergence performance. Specifically, in the ZDT3 test, the IGD metric improved by 7.7% and the SP metric was optimized by 63.4%, while the best HV value of 0.28037 was achieved in the UF4 test. Comprehensive case studies validate the effectiveness of the proposed approach under this ideal setting. Under normal conditions, the strategy successfully eliminates power and thermal deficits of 1120.00 kW and 124.46 kW, respectively, at 19:00. It achieves this through optimal quota allocation, which involved allocating 468.19 kW of electricity at 13:00 and 65.78 kW of thermal energy at 18:00. Under extreme weather, the strategy effectively converts 95.87 kW of electricity to thermal energy at 18:00. This conversion addresses a 444.46 kW thermal deficit. Furthermore, the implementation reduces microgrid cluster trading imbalances from 1300 kW to zero for electricity and from 400 kW to 176.34 kW for thermal energy, significantly enhancing system economics and multi-energy coordination efficiency. This research provides valuable insights and methodological support for advanced microgrid optimization by establishing a performance benchmark, with future work focusing on integration with forecasting techniques. Full article

Accurate extraction of single-diode photovoltaic (PV) model parameters is essential for reliable performance prediction and diagnostics, yet five-parameter identification from I-V data is ill-posed and computationally expensive. To develop and validate a hybrid analytical–metaheuristic approach that derives the diode ideality factor, saturation current, and photocurrent analytically while optimizing only series and shunt resistances, thereby reducing computational cost without sacrificing accuracy. I-V datasets were collected from a 9.54 kW grid-connected PV installation in Algiers, Algeria (15 operating points; 747–815 W m⁻²; 25.4–28.4 °C). Nine metaheuristics—Stellar Oscillation Optimizer, Enzyme Action Optimization, Grey Wolf Optimizer, Whale Optimization Algorithm, Cuckoo Search, Owl Search Algorithm, Improved War Strategy Optimization, Rüppell’s Fox Optimizer, and Artificial Bee Colony—were benchmarked against full five-parameter optimization and a Newton–Raphson baseline, using root-mean-squared error (RMSE) as the objective and wall-time as the efficiency metric. The hybrid scheme reduced the decision space from five to two parameters and lowered computational cost by ≈60–70% relative to full-parameter optimization while closely reproducing measured I-V/P-V curves. Across datasets, algorithms achieved RMSE ≈ 2.49 × 10⁻² − 2.78 × 10⁻². Rüppell’s Fox Optimizer offered the best overall trade-off (lowest average RMSE and fastest runtime), with Whale Optimization Algorithm a strong alternative (typical runtimes ≈ 107–112 s). Partitioning identification between closed-form physics and light-weight optimization yields robust, accurate, and efficient PV parameter estimation suitable for time-sensitive or embedded applications. Dynamic validation using 1498 real-world measurements across clear-sky and cloudy conditions demonstrates excellent performance: current prediction $R^2=0.9882$, power estimation $R^2=0.9730$, and voltage tracking $R^2=0.9613$. Comprehensive environmental analysis across a 39.2 °C temperature range and diverse irradiance conditions ($0\text{–}1014 \mathrm{W}/{\mathrm{m}}^2$) validates the method’s robustness for practical PV monitoring applications. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a multifactorial condition requiring multi-target therapeutic strategies beyond traditional single-marker approaches. In this work, we present a fully in silico nutraceutical screening pipeline that integrates molecular prediction, systemic aggregation, and technological design. A curated panel of ten MASLD-relevant targets, spanning nuclear receptors (FXR, PPAR-α/γ, THR-β), lipogenic and cholesterogenic enzymes (ACC1, FASN, DGAT2, HMGCR), and transport/regulatory proteins (LIPG, FABP4), was assembled from proteomic evidence. Bioactivity records were extracted from ChEMBL, structurally standardized, and converted into RDKit descriptors. Predictive modeling employed a stacked ensemble of Random Forest, XGBoost, and CatBoost with isotonic calibration, yielding robust performance (mean cross-validated ROC-AUC 0.834; independent test ROC-AUC 0.840). Calibrated probabilities were aggregated into total activity (TA) and weighted TA metrics, combined with structural clustering (six structural clusters, twelve MOA clusters) to ensure chemical diversity. We used physiologically based pharmacokinetic (PBPK) modeling to translate probabilistic profiles into minimum simulated doses (MSDs) and chrono-specific exposure (%T>IC50) for three prototype concepts: HepatoBlend (morning powder), LiverGuard Tea (evening aqueous form), and HDL-Chews (postprandial chew). Integration of physicochemical descriptors (MW, logP, TPSA) guided carrier and encapsulation choices, addressing stability and sensory constraints. The results demonstrate that a computationally integrated pipeline can rationally generate multi-target nutraceutical formulations, linking molecular predictions with systemic coverage and practical formulation specifications, and thus provides a transferable framework for MASLD and related metabolic conditions. Full article

The systematic analysis of the synergistic mechanism between microbial fiber-degrading enzymes and short-chain fatty acids under high-fiber diet conditions is limited. In this study, we evaluated the effects of a high-fiber diet on the growth performance, nutrient digestibility, blood and serum metrics, cellulase/hemicellulase activity, and fecal microbial composition of growing Tibetan pigs. Forty Tibetan pigs were allocated to a control group (CON, the diet contains 5% crude fiber) or a high-fiber group (HF, the diet contains 10% crude fiber) based on crude fiber levels as a blocking factor. The pre-trial period was 7 d, and the formal trial lasted 28 d. CON group and HF group showed no effect on growth performance and nutrient apparent digestibility (p > 0.05). The HF group showed significantly higher fecal cellulase and hemicellulase activities than those of the CON group (p < 0.05). Additionally, the HF group showed significantly elevated levels of acetic, propionic, and butyric acids, as well as increased relative abundances of Fibrobacter and p-75-a5 in the feces (p < 0.05). The correlation analysis revealed that Fibrobacter exhibited significant positive correlations with acetic acid, butyric acid, cellulase, and hemicellulase, whereas p-75-a5 was significantly positively correlated with hemicellulase (p < 0.05). In conclusion, this study provides strong evidence that the efficient utilization of dietary fiber by Tibetan pigs results from highly specialized microbial mechanisms in their large intestine, as reflected by their fecal microbiota composition. Fibrobacter and p-75-a5 play a crucial role in enabling these pigs to utilize fiber effectively. Certain specific microbiota secrete a greater quantity of enzymes to facilitate the decomposition of dietary fiber, and this process ultimately leads to the generation of more metabolites. Full article

Background: Cytochrome P450 (CYP450) enzymes play a central role in the metabolism of xenobiotics, including plant-derived compounds such as terpenoids. Objectives: This study aimed to predict the molecular interactions of linalool (LIN) and linalyl acetate (LINAct), major constituents of lavender essential oil, with the canine CYP2B11, CYP2C21, and CYP2D15 isoforms, using in silico approaches. Methods: Three-dimensional (3D) models of the target enzymes were generated through homology modeling using SWISS-MODEL and validated based on global model quality estimate (GMQE) and QMEAN Z-score metrics. Ligand structures were optimized in the Molecular Operating Environment (MOE), and pharmacophoric features were analyzed. Molecular docking simulations were performed using AutoDock Vina, followed by visualization of interactions in MOE. Results: LIN and LINAct exhibit favorable binding affinities with all three isoforms, suggesting their potential as substrates or modulators. Hydrogen bonding and hydrophobic interactions were the predominant forces stabilizing the ligand–enzyme complexes. Conclusions: These findings provide a computational basis for understanding the hepatic metabolism of LIN and LINAct in dogs, offering preliminary insights into the role of specific CYP isoforms in their biotransformation. Full article

Background: Ambulatory blood pressure monitoring (ABPM) is increasingly recognized as a more reliable indicator of blood pressure status in children than clinic-based measurements, with superior predictive value for cardiovascular morbidity and mortality. However, evidence on the clinical utility of ABPM-derived indices, such as pulse pressure (PP), pulse pressure index (PPI), rate pressure product (RPP), ambulatory arterial stiffness index (AASI), and average real variability (ARV), remains underexplored in the pediatric population, particularly among children with chronic kidney disease (CKD). Objective: To evaluate the correlation between ABPM-derived indices in children, with a subgroup analysis comparing those with and without CKD. Secondary objectives included identifying factors associated with AASI and ARV and assessing their utility in cardiovascular risk stratification. Methods: In this bicentric cross-sectional study, 70 children (41 with CKD and 29 controls) were enrolled. ABPM indices (PP, PPI, RPP, AASI, and ARV) were calculated, and both descriptive and inferential statistical analyses, including linear regression, were performed. Results: Systolic and diastolic hypertension were significant predictors of elevated ARV (p < 0.05), while body mass index (BMI) and glomerular filtration rate (GFR) were positively associated with AASI (p < 0.05). Use of angiotensin-converting enzyme inhibitors (ACEIs) was associated with reduced arterial stiffness (p = 0.02). Significant differences were observed in weight, BMI, PP, and PPI between the CKD and non-CKD groups, with ABPM demonstrating greater sensitivity in detecting vascular health markers. Conclusions: ABPM-derived indices, particularly PP, PPI, and ARV, show promise in improving cardiovascular risk assessment in children. These findings support the broader use of ABPM metrics for refined cardiovascular evaluation, especially in pediatric CKD. Full article

Background: Aquaculture increasingly seeks sustainable alternatives to fishmeal, a key protein source in fish diets. Black Soldier Fly Larvae (BSFL) meal is a promising substitute, but its effects on fish growth, immunity, and gut health need further investigation. This study aimed to evaluate the impact of varying BSFL inclusion levels on juvenile hybrid grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂), a widely farmed species in tropical aquaculture. Methods: Juvenile hybrid grouper were fed diets with four levels of BSFL substitution (0%, 10%, 30%, and 50%) over 56 days. Key metrics such as growth performance, immune function, antioxidant capacity, and gut transcriptome were analyzed. Results: Replacing fish meal with BSFL meal had no significant effect on the survival rate of hybrid grouper (p > 0.05) but significantly affected growth performance, immune function, and antioxidant capacity (p < 0.05). BSFL10 and BSFL30 groups showed good growth and elevated immune enzyme activity, with significantly higher HIS levels (p < 0.05); the Wf of the BSFL10 group was comparable to the control. However, excessive replacement (BSFL50) led to reduced growth (Wf significantly lower, p < 0.05) and increased oxidative stress, as indicated by higher CAT activity (p < 0.05). Transcriptomic analysis revealed upregulation of immune- and metabolism-related genes with increasing BSFL levels, with immune pathways notably activated in the BSFL50 group. Conclusions: BSFL meal is a promising alternative to fishmeal in juvenile hybrid grouper diets, with moderate inclusion (10–30%) being most beneficial. Excessive BSFL substitution (50%) may impair fish health, highlighting the need for careful formulation in aquaculture diets. Full article

The shift toward plant-based feeds in aquaculture necessitates a search for probiotics to improve the digestibility of such feeds and fish growth. This study characterizes four Bacillus strains for their probiotic potential in carp (Cyprinus carpio). Strains isolated from river sediments underwent in vitro screening for proteolytic/amylolytic activity, antibiotic sensitivity, and biofilm formation. Whole-genome sequencing was performed and functional annotation identified probiotic-related genes. All strains were identified as Bacillus velezensis and harbored genes providing thermal, osmotic, and oxidative stress resistance, alongside enzymes and bioactive metabolite synthesis pathways. Two non-antagonistic strain pairs were solid-phase cultivated on soybeans and incorporated into carp feed (0.1% w/w) for a 76-day trial, and growth metrics and gene expression were analyzed in juvenile fish. Group 1 (strains MT14 + MT42) exhibited a 40.75% higher biomass increase than the control group while Group 2 (strains MT141 + MT142) exhibited a 56.62% higher biomass growth. No significant gene expression changes occurred in juveniles, though MT141 + MT142 transiently modulated fry expression profiles. Therefore, these Bacillus velezensis strains synergistically enhance growth in carp that are fed plant-rich diets, highlighting their viability as aquaculture probiotics. Full article

Advancements in biosensing technologies have introduced opportunities for non-invasive, real-time monitoring of salivary biomarkers, enabling progress in fields ranging from personalized medicine to public health. Identifying and prioritizing the most critical analytes to measure in saliva is essential for estimating physiological status and forecasting performance in applied contexts. This study examined the value of 12 salivary analytes, including hormones, metabolites, and enzymes, for predicting cognitive and physical performance outcomes in military personnel (N = 115) engaged in stressful laboratory and field tasks. We calculated a series of features to quantify time-series analyte data and applied multiple regression techniques, including Elastic Net, Partial Least Squares, and Random Forest regression, to evaluate their predictive utility for five outcomes of interest: the ability to move, shoot, communicate, navigate, and sustain performance under stress. Predictive performance was poor across all models, with R-squared values near zero and limited evidence that salivary analytes provided stable or meaningful performance predictions. While certain features (e.g., post-peak slopes and variance metrics) appeared more frequently than others, no individual analyte emerged as a reliable predictor. These results suggest that salivary biomarkers alone are unlikely to provide robust insights into cognitive and physical performance outcomes. Future research may benefit from combining salivary and other biosensor data with contextual variables to improve predictive accuracy in real-world settings. Full article