Saved Queries

by Areli J. Hernandez-Guzman, Daniel M. Paredes, Fabricio G. Méndez-Landín, Alejandro Vega-Ríos, Marilia Guillén, Erick Roberto Bandala, Martín Pacheco-Álvarez, Rosmary Guillén, Patricio J. Espinoza-Montero, Miguel A. Sandoval-Lopez and Oscar Manuel Rodriguez-Narvaez

Processes 2026, 14(18), 2899; https://doi.org/10.3390/pr14182899 - 11 Sep 2026

Abstract

Recalcitrant azo dyes in textile wastewater are a significant environmental concern due to their persistence and potential impacts on human and ecosystem health. Heterogeneous Fenton-like processes offer a promising approach for their removal, although catalyst performance depends strongly on the physicochemical characteristics of the active material. This study investigated Fe-functionalized silicon oxide (Fe-SiO) catalysts for sodium percarbonate (SPC)-activated removal of Reactive Orange 84 (RO84). The catalysts were prepared using silicon oxide supports with and without thermochemical pretreatment and different amounts of Fe during synthesis. Their structural, morphological, and elemental characteristics were evaluated by transmission electron microscopy (TEM), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (EDS), complemented by textural analysis. Increasing the amount of Fe used during synthesis shifted removal from adsorption-influenced to oxidation-associated, as reflected in the kinetic behavior. Thermochemical pretreatment promoted more homogeneous Fe dispersion and reduced aggregation in the S2 series, consistent with its higher catalytic response under several evaluated conditions. The PFO model empirically described the observed removal kinetics. Overall, the Fe-SiO materials showed potential for SPC-assisted RO84 removal under the evaluated conditions. Full article

(This article belongs to the Section Chemical Processes and Systems)

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20 pages, 1596 KB

Open AccessArticle

Anthranilate Reduces Pseudomonas aeruginosa Infection Severity through an Antibiotic-Independent Anti-Virulence Mechanism

by Huiyan Li, Min-Hee Kang, Wen-Xin Niu, Eunsoo Kim and Joon-Hee Lee

Antibiotics 2026, 15(9), 898; https://doi.org/10.3390/antibiotics15090898 - 11 Sep 2026

Abstract

Background/Objectives: Antibiotic resistance is a growing global health challenge, especially with tricky bacteria like Pseudomonas aeruginosa. Anthranilate, previously identified as a signaling molecule in P. aeruginosa, modulates various pathogenicity-related phenotypes by reducing virulence factor production, inhibiting biofilm formation, and increasing antibiotic susceptibility. Based on these good properties as an anti-virulence agent, this study evaluated the actual therapeutic potential of anthranilate using mouse skin infection and lung infection models. Specifically, the efficacy of anthranilate in a standalone treatment was investigated without reliance on conventional antibiotics. Methods: The therapeutic efficacy of anthranilate was evaluated in murine skin and lung infection models of P. aeruginosa. Anthranilate was administered as a standalone treatment, and its effects on bacterial burden, inflammatory responses, and tissue lesion progression were assessed and compared with those of gentamicin treatment. Results: Anthranilate effectively reduced bacterial suppuration, mitigated inflammatory responses, and suppressed lesion progression in infected skin and lung tissues. Notably, anthranilate alone produced therapeutic effects comparable to those of gentamicin. Conclusions: These findings highlight its potential of standalone treatment as an alternative to traditional antibiotics and offer a novel anti-virulence strategy that minimizes selective pressure for resistance development. Full article

(This article belongs to the Special Issue New Insights Toward the Development of Novel Inhibitors of S. aureus and P. aeruginosa Factors)

29 pages, 13891 KB

Open AccessArticle

Study on the Optimization of Laser Cladding Process Parameters and Overlap Strategies for CuCrZr Copper Alloy Powders

by Jinsu Yu, Duc Anh Le, Chao Zhang and Ji Zhao

Materials 2026, 19(18), 3887; https://doi.org/10.3390/ma19183887 - 11 Sep 2026

Abstract

The quality of laser cladding is influenced by a combination of various process parameters, including laser power, powder feed rate, scanning speed, defocus amount, overlap ratio, and the flow rates of the powder feed gas and shielding gas. Taking into account the adjustment characteristics of laser cladding equipment, this paper selects laser power, powder feed rate, and scanning speed as the primary factors of study and systematically analyzes the patterns of their effects on the quality of the cladding layer. Based on the results of preliminary experiments, a single-factor experimental design was formulated, and the experimental results were analyzed according to the established cladding quality evaluation system. By developing an orthogonal experimental design and employing a combination of range analysis and analysis of variance, the optimal combination of process parameters was determined. Subsequently, the overlap ratio and Z-axis lift were derived and calculated using the equal-area method, providing a reference for the rapid estimation of multi-pass and multi-layer cladding coating process Windows. Full article

(This article belongs to the Section Manufacturing Processes and Systems)

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26 pages, 6833 KB

Open AccessArticle

A Multimodal AI Framework for Medical Education: Integrating Adaptive Image Retrieval, Fast Synthesis, and LLM-Based Clinical Auditing

by Miguel Díaz-Benito, Cecilia Diana-Albelda, Álvaro García-Martín, Mario Rubén Paz Campos and Jesus Bescos

J. Imaging 2026, 12(9), 438; https://doi.org/10.3390/jimaging12090438 - 11 Sep 2026

Abstract

Access to reliable medical images is essential for clinical training. To address this need, this paper presents an extended version of MIRAGE, a multimodal retrieval and generation system that utilizes a shared latent space to process medical queries by retrieving real images from the ROCO dataset, generating synthetic scans, and providing LLM-based clinical descriptions alongside dual-concept visual comparisons. To overcome previous computational limits and the lack of clinical validation, we introduce three core enhancements: first, an Auto-

α

module to dynamically weight visual and textual similarities; second, the integration of LCM-LoRA to accelerate synthetic image generation; and third, an automated clinical auditor based on Gemini 2.5 Flash. Experimental results demonstrate that Auto-

α

improves retrieval accuracy for heterogeneous queries, reaching

38.83

% Top-1 Recall over a 65,419-image gallery and outperforming nine fusion baselines evaluated under a unified configuration, with a controlled ablation attributing most of this gain to learning the weight rather than merely making it query-adaptive, while the LCM-LoRA module reduces computational costs by a factor of 12.5× in CPU environments, with a blinded radiologist evaluation confirming only a small drop in clinical quality. Furthermore, the clinical auditor achieves a 0.805 Pearson correlation against an expert radiologist, effectively correcting the systematic overestimation of traditional CLIP scores. Finally, the optimized platform is publicly deployed on Hugging Face. Full article

(This article belongs to the Section Medical Imaging)

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24 pages, 1771 KB

Open AccessArticle

Carbendazim Transport and Interactions with Regenerated Cellulose Membranes Probed by Analytical Diafiltration

by Hernán Valle, Verónica Izquierdo and Manuel Palencia

Sci 2026, 8(9), 254; https://doi.org/10.3390/sci8090254 - 11 Sep 2026

Abstract

Carbendazim (CBDZ) is widely used for the prevention and control of fungal diseases in agricultural crops. Its extensive and recurrent application may lead to the occurrence of residues in agricultural environments and increase the potential for contamination of aquatic systems. In this study, analytical diafiltration was used to investigate the transport and interfacial association of CBDZ with regenerated cellulose membranes (CELms) rather than to evaluate size-exclusion-based pesticide removal. Continuous diafiltration experiments using the washing mode were performed with an 8.0 ppm CBDZ solution and 10 kDa of CELm at different pH values (3.0–9.0), while permeate flow rate and CBDZ concentration in successive permeate fractions were monitored throughout the process. CBDZ membrane retention (Rm) ranged from (7.4 ± 3.3%) at pH 9.0 to (23.2 ± 2.0%) at pH 3.0, with a maximum membrane-associated amount (\(R_m^{max}\) ) of 478 μg CBDZ per g of CELm. The pH dependence of Rm was accurately described by Rm = 24.9740 + 0.1814 ph − 0.2375 ph² for 3.0 ≤ pH ≤ 9.0 (r² = 0.999). The results are consistent with adsorption-mediated interfacial association, mainly involving physicochemical interactions with hydroxyl- and carboxyl-containing functionalities of CELms, while electrostatic interactions contributed less than 3.0% within the pH range of 6.0–7.0. The diafiltration profiles were successfully described by the ExDM–IDZ model. The parameters governing the shape of the retention profile were Rm, associated with the horizontal asymptote, and (j), which describes the decay rate and was related to the evolution of CBDZ concentration and its apparent residence behavior during diafiltration. Overall, these results demonstrate that analytical diafiltration provides a useful framework for investigating the transport, partitioning, and adsorption-mediated interactions of low-molecular-weight, water-soluble pesticides with membrane materials. Full article

(This article belongs to the Section Environmental and Earth Science)

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35 pages, 9197 KB

Open AccessArticle

Data-Driven Position Control of a McKibben Pneumatic Artificial Muscle: Simulation and Experimental Validation of PID and LQI Controllers

by Tomislav Bazina, Luka Kopajtić, Ervin Kamenar and Goran Gregov

Actuators 2026, 15(9), 484; https://doi.org/10.3390/act15090484 - 11 Sep 2026

Abstract

Pneumatic artificial muscles, including McKibben-type actuators, offer high power-to-weight ratio, compliance, and inherent safety, but their nonlinear pressure–contraction behavior, hysteresis, saturation, and load-dependent dynamics make accurate position control challenging. This study develops a practical data-driven workflow that derives a branchwise feedforward compensator and an LQI or PID controller from one open-loop characterization experiment. Quasi-static characterization first identifies a conservative control-ready voltage window. A bounded random excitation within this window is replayed with

4 s

holds to expose terminal and transient behavior. The same experiment supplies branchwise discrete plant models and a feedforward lookup. Two open-loop-derived transient layers, voltage creep compensation and dynamic pressure referencing, are applied to the raw lookup before simulation. Four controller variants are compared on a common simulated closed-loop benchmark built from the identified plant: a feedforward-only baseline, a branchwise proportional–integral–derivative (PID) baseline, a base linear quadratic integral (LQI) controller with displacement and pressure feedback, and a velocity-state LQI extension with a filtered velocity estimate. A multi-metric optimization score balances tracking RMS, settled oscillation, command activity, saturation, and gain magnitude. The score selects the base LQI within the LQI family. The selected gains and transient layers are deployed in a real-time implementation with manually reduced position gains. The controllers are then evaluated on a common reference stream against the physical actuator. Although simulation metrics cannot be transferred directly to the real system, the combined-metric ranking of the controllers remains unchanged. Full article

(This article belongs to the Special Issue Human-Centric Intelligent Actuation Systems: Innovations in Control, Sensing, and Multidisciplinary Applications)

16 pages, 362 KB

Open AccessArticle

Evaluation of Grazing Behavior and Its Associations with Obesity, Emotion Regulation Difficulties, and Problematic Smartphone Use in Adolescents with Essential Hypertension

by Gunes Isik, Cansu Mercan Isik and Masum Ozturk

Children 2026, 13(9), 1233; https://doi.org/10.3390/children13091233 - 11 Sep 2026

Abstract

Background: This study aimed to compare grazing behavior scores between adolescents with essential hypertension (HTN) and controls. It also investigated the associations of grazing behavior with obesity, emotion regulation difficulties (ERD), problematic smartphone use, and screen time. Methods: This cross-sectional case–control study enrolled 60 adolescents with essential HTN and 60 controls selected via frequency matching based on age and sex, all aged 12–18 years. The diagnosis of essential HTN was confirmed using 24-h ambulatory blood pressure monitoring (ABPM). Grazing behavior, ERD, problematic smartphone use, screen time and body mass index (BMI) were assessed in all participants. Group comparisons and associations between grazing behavior and the study variables were analyzed. Results: The essential HTN and control groups were comparable with respect to age and sex distribution (p > 0.05). The mean BMI in the essential HTN group was 31.18 ± 6.81 kg/m², which was significantly higher than that in the control group (23.35 ± 4.47 kg/m²) (p < 0.001). A significant positive correlation was found between total Grazing Questionnaire (GQ) scores and BMI (r = 0.252; p = 0.006), ERD (r = 0.187; p = 0.041), and problematic smartphone use (r = 0.315; p < 0.001). A statistically significant difference was observed between the essential HTN and control groups in total GQ scores [F(1, 117) = 4.85, p = 0.030, η²p = 0.040]. After adjustment for BMI, participants with hepatic steatosis had significantly higher total GQ scores (p = 0.019, η²p = 0.138), Grazing Behaviors subscale scores (p = 0.046, η²p = 0.107), and Uncontrollability subscale scores (p = 0.025, η²p = 0.123) than those without hepatic steatosis. Conclusions: Adolescents with essential HTN had higher grazing behavior scores than controls after adjustment for BMI. Grazing behavior was also associated with ERD and problematic smartphone use across the study sample. The findings regarding grazing behavior and hepatic steatosis warrant cautious interpretation, as the subgroup analysis was exploratory and included a relatively small number of participants. Full article

(This article belongs to the Section Pediatric Nephrology & Urology)

27 pages, 8011 KB

Open AccessArticle

Learning Thermospheric State Evolution: An Adaptive Neural Operator Framework Based on TIE-GCM Simulations

by Shuyang Zhou, Changyong He, Dunyong Zheng and Dongfang Lin

Remote Sens. 2026, 18(18), 3134; https://doi.org/10.3390/rs18183134 - 11 Sep 2026

Abstract

Reliable short-term prediction of thermospheric states is important for satellite drag applications but remains difficult because of nonlinear, multiscale variability. We developed a multivariable Adaptive Fourier Neural Operator (AFNO) surrogate using 24 years (2000–2023) of Thermosphere–Ionosphere Electrodynamics General Circulation Model (TIE-GCM) simulations. The model predicts neutral density, temperature, winds, and geopotential height over 24-h autoregressive forecasts. We compared direct state prediction with increment-based flow prediction and tested logarithmic density scaling and one-hour historical inputs. Both formulations preserved dominant large-scale density structures and the equatorial mass density anomaly, with anomaly correlation coefficients above 0.94 for all variables. The Direct formulation maintained lower errors and greater stability at longer lead times, whereas Flow performed better only at early steps. Logarithmic density scaling produced variable- and altitude-dependent trade-offs, and historical inputs yielded no overall benefit. During a representative geomagnetic storm, the baseline reproduced broad density morphology but increasingly underestimated enhancement magnitude with lead time. Because evaluation used the independent 2023 TIE-GCM test year with prescribed forecast-time forcing and no observational validation, the framework should be interpreted as a TIE-GCM-consistent surrogate rather than a validated predictor of the observed thermosphere. Full article

(This article belongs to the Special Issue Satellite Observations and Numerical Studies for Ionosphere, Plasma Dynamics, and Space Weather Prediction)

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15 pages, 2287 KB

Open AccessArticle

Identification and Validation of Reliable Reference Genes for Gene Expression Studies in Postharvest Atemoya Pulp (Annona cherimola Mill × A. squamosa L.) Subjected to Different Preservation Treatments

by Xueyu Zhang, Qinyi Gao, Ying Zhou, Hanzhou Zhang, Zhihui Chen and Jingjing Chen

Int. J. Mol. Sci. 2026, 27(18), 8114; https://doi.org/10.3390/ijms27188114 - 11 Sep 2026

Abstract

Quantitative real-time PCR (qRT-PCR) is a widely used technique for quantifying gene expression. However, accurate data normalization requires stable reference genes that exhibit constant expression levels across different experimental conditions. To date, no suitable reference genes have been validated for atemoya fruits (Annona cherimola Mill × A. squamosa L.). This study aimed to evaluate the expression stability of candidate reference genes in atemoya across distinct tissues, postharvest storage stages, and various treatment conditions. To this end, we designed specific primers for six reference genes: ubiquitin carrier-like protein (UBC), actin 7 (ACT7), actin 11 (ACT11), elongation factor 1α (EF1α), 18S ribosomal RNA (18S), and β-tubulin (TUB). Total RNA was extracted from atemoya tissues (e.g., petals, young fruits, and roots), for pulp across three post-harvest time points (0, 2, and 4 days) and under different conditions: 28 °C, 15 °C, ethylene, or 1-MCP treatment. The geNorm tool was subsequently used to identify the most stable reference transcripts under each experimental condition. ACT7 was the most stable reference gene across atemoya tissues, while UBC ranked first under all postharvest conditions tested (28 °C storage, 15 °C cold storage, ethylene, and 1-MCP). Furthermore, the suitability of these reference genes under ethylene and 1-MCP treatments was validated by examining the expression patterns of AaPG and AaERF. Collectively, the combined use of ACT7, UBC, and 18S proved to be the most reliable normalization strategy across all experimental conditions. This validated multi-gene approach provides a robust foundation for future investigations into gene expression and the postharvest ripening mechanisms of atemoya. Full article

(This article belongs to the Special Issue Molecular Breeding and Comprehensive Utilization of Economic Crops)

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27 pages, 10849 KB

Open AccessArticle

Deep Learning for Schatzker Classification on Anteroposterior Radiographs: A Controlled Benchmark and a Transferable Control Protocol

by Sang Hyun Na and So Hyun Ahn

J. Clin. Med. 2026, 15(18), 7075; https://doi.org/10.3390/jcm15187075 - 11 Sep 2026

Abstract

Background/Objectives: Schatzker type is assigned early, usually from the anteroposterior (AP) radiograph. A single benchmark accuracy cannot say whether a model read the fracture, the anatomy around it, the annotation, or how the archive was assembled. We ran four inexpensive controls to separate those contributions. Methods: We benchmarked a ResNet-50 on PlaTiF, a 2026 public release built for artificial-intelligence research that pairs 421 AP knee radiographs from 186 patients with expert Schatzker labels and per-image tibial segmentations. Evaluation used stratified group five-fold cross-validation grouped by patient, five seeds and balanced accuracy. Inputs were cropped to the expert tibial segmentation shipped with the dataset, an oracle localisation unavailable at deployment. Four controls ran on identical folds: a regression given no pixel content; ablation of the tibial pixels with its complement; a regression on the expert mask alone; and an augmentation audit for label-erasing invariances. Results: Among the 128 fracture patients the network reached 0.345 ± 0.030 six-class balanced accuracy, +0.168 over a non-anatomical baseline fitted on the same folds and the same labels (95% CI +0.106 to +0.230, p = 0.002). Recall was graded: 0.72 for Schatzker VI, 0.11 for V and 0.04 for IV, the last two below chance (0.167). Erasing the tibial pixels left 0.257 ± 0.025, read on its own as the target bone being unused; its complement, the tibia with everything else removed, reached 0.367 ± 0.012, and the whole radiograph, which carries both, only 0.297 ± 0.032 (+0.071 for the tibia alone, 95% CI +0.031 to +0.111, p = 0.008). A regression on the expert mask alone reached 0.213 ± 0.034 and was not distinguishable from the erased model. On fracture versus no classifiable fracture the network reached 0.833 ± 0.028 against 0.814 ± 0.016 for a model given no pixels (p = 0.264), and a coronal computed tomography section accompanied 126 of 128 fracture patients but 24 of 58 others (p = 2.9 × 10⁻¹⁹). Conclusions: Each headline number admitted an explanation other than the fracture in the target bone. An ablation reported without its complement misstated where the signal lay, and an augmentation audit overturned our own explanation for the failure of type IV. Controls of this kind cost minutes, and this study illustrates why they can be informative when a benchmark is built on a retrospective clinical archive. Full article

(This article belongs to the Special Issue Artificial Intelligence in Orthopedics: Current Advancements and Future Perspectives)

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18 pages, 1515 KB

Open AccessArticle

Intelligent Synchronization of Machine Learning Models Using Graph Neural Networks: Application to Flood Prediction

by Boban Temelkovski, Rexhep Mustafovski, Jugoslav Achkoski, Georgi Dimirovski and Mile Stankovski

Future Internet 2026, 18(9), 474; https://doi.org/10.3390/fi18090474 - 11 Sep 2026

Abstract

Flood prediction remains a critical challenge in environmental risk management and disaster preparedness. Accurate river-level forecasting is essential for the development of reliable early warning systems and the mitigation of flood-related risks. However, conventional ensemble approaches, such as averaging and majority voting, often exhibit limited adaptability when individual models respond differently to anomalies or incomplete data. To address this limitation, this study proposes a graph-based synchronization framework that integrates XGBoost and Random Forest models using a Graph Convolutional Network (GCN). The proposed framework represents the outputs of the base prediction models as graph nodes and employs graph message passing to learn context-dependent relationships between their predictions. The framework is evaluated using real-world hydrological observations from the Lepenec River Basin in North Macedonia together with meteorological data obtained from the OpenWeatherMap API. Experimental results demonstrate that the proposed GCN-based synchronization framework outperforms both the standalone prediction models and the previously proposed linear synchronization method, achieving an R² value of 0.91 and a Mean Absolute Error (MAE) of 0.21. The obtained results indicate that graph-based synchronization provides an adaptive approach for integrating heterogeneous machine-learning models and has the potential to support future flood early-warning systems and intelligent environmental monitoring applications. Full article

(This article belongs to the Section Smart System Infrastructure and Applications)

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21 pages, 7360 KB

Open AccessArticle

Solvothermal Synthesis and Carbon Capture Performance of Terephthalate-Linked Zn_0.75Mg_0.25 MOF-74: Effects of Synthesis Conditions on Structure and CO₂ Adsorption

by Siyabonga Brighton Ndebele, Glory Makuwa, Djemima Bulanga, Thembelihle Masombuka and Major Mabuza

Clean Technol. 2026, 8(5), 152; https://doi.org/10.3390/cleantechnol8050152 - 11 Sep 2026

Abstract

Coal-fired power generation remains a major source of carbon dioxide (CO₂) emissions, and metal–organic framework-74 (MOF-74) materials offer high adsorption capacity but rely on costly 2,5-dihydroxyterephthalic acid linkers that limit scalability. This study synthesized bimetallic Zn_0.75Mg_0.25-MOF-74 using terephthalic acid (TPA) as a cheaper alternative linker and evaluated the effect of synthesis reaction temperature (89–160 °C) and time (5–55.5 h) on its physicochemical properties for carbon capture. Samples were prepared solvothermally and characterized by FTIR, XRD, SEM-EDS, and N₂ (77 K) and CO₂ (293 K) adsorption analysis. FTIR confirmed metal–ligand coordination; XRD verified crystalline MOF-74 formation, and SEM showed well-defined rod-like morphology at 100 °C, 12 h and 125 °C, 30 h. Direct CO₂ adsorption on the 125 °C, 30 h sample yielded a Type I isotherm characteristic of micropore filling, with an uptake of 0.31 mmol/g at ~1 bar and 0.072 mmol/g at flue-gas-relevant conditions (~0.135 bar). Its CO₂-derived BET surface area (60.10 m²/g) and Dubinin–Astakhov micropore area (131.69 m²/g) far exceeded N₂-derived values, confirming ultra-micropores accessible to CO₂ but not to N₂ at 77 K. TPA therefore yields a stable, microporous CO₂-adsorbing framework, trading some capacity for lower cost and scalability. Future investigations should systematically evaluate long-term cycling stability and adsorption performance under mixed-gas operating conditions. Full article

(This article belongs to the Special Issue Green Solvents and Materials for CO₂ Capture, 2nd Edition)

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27 pages, 926 KB

Open AccessArticle

Low n-3/High n-6 Flaxseed and Hermetia illucens Larvae Oils as Feed Materials: Effects on In Vitro Rumen Fermentation, Maternal Metabolism, Antioxidant Status and Colostrum in Prolific Ewes

by Kamila Lewandowska, Natalia Pachura-Hanusek, Anna Burek, Antoni Szumny and Robert Kupczyński

Int. J. Mol. Sci. 2026, 27(18), 8111; https://doi.org/10.3390/ijms27188111 - 11 Sep 2026

Abstract

Black soldier fly larvae (BSFL; Hermetia illucens) oil and flaxseed oil provide contrasting fatty acid profiles and may serve as alternative lipid feed materials in ruminant nutrition. This study assessed low-α-linolenic/high-linoleic flaxseed oil, BSFL oil, and their blends using an in vitro rumen fermentation screening with pooled bovine rumen inoculum and a randomized prepartum feeding trial in 32 twin- or triplet-bearing Olkuska ewes. In vitro, the single oils and a 1:1 blend were evaluated at two inclusion levels; total VFA concentration was unchanged, whereas propionate proportion, the acetate-to-propionate ratio, methane, ammonia, and incubation-fluid fatty acid profiles showed treatment-dependent responses. In vivo, an unsupplemented control was compared with flaxseed oil, BSFL oil, and a 2:1 blend supplied at 30 g/day for 21 days before expected parturition. Colostrum fat concentration differed among treatments (p = 0.036); the 2:1 blend group had a higher value than the control group (11.29% vs. 8.26%; Dunnett-adjusted p < 0.05), while major fatty acid classes did not differ. Supplementation was also associated with differences in selected minor colostrum fatty acids and several serum metabolic variables. Colostrum yield was not measured; therefore, this finding reflects fat concentration rather than total colostrum fat output. Serum total antioxidant status (TAS) was unaffected, while a treatment-by-time interaction was observed for γ-glutamyl transferase. The tested plant- and insect-derived oils therefore modified ruminal lipid transformations and selected maternal and colostrum traits without a detectable change in TAS. Full article

(This article belongs to the Special Issue Molecular Insights into Animal Nutrition: Oxidative Stress, Polyphenols and Functional Feed Materials)

29 pages, 3610 KB

Open AccessArticle

Biological Properties of Eucalyptus globulus Oil and Eucalyptol, Chemical Composition and Molecular Docking

by Ilyass Lkhalidi, Aimad Allali, Hamza Saghrouchni, Mohamed Chebaibi, Rachid Flouchi, Ibrahim Mssillou, Ana Tomić, Asaad Khalid, Abdelkrim Agour, Youness El Abdali, Issam Ghabbour and Moulay Larbi Ouahidi

Biophysica 2026, 6(5), 88; https://doi.org/10.3390/biophysica6050088 - 11 Sep 2026

Abstract

Background: Moroccans employ Eucalyptus globulus Labill., a medicinal herb, to cure a variety of ailments. This research aimed to evaluate the chemical constituents of Eucalyptus globulus essential oil (EGEO) to determine their composition and potential use as hemolytic, antioxidant, and antimicrobial agents. Methods: GC analysis was utilized to determine the composition of EGEO harvested in the province of Meknes. Using the disk diffusion technique, MIC, MBC, and MFC tests, antibacterial and antifungal activity were assessed against pathogenic microorganisms. DPPH, TAC, and FRAP experiments were used to evaluate the antioxidant potential of EGEO and Eucalyptol. The main chemical binding affinities were predicted by Molecular Docking analysis. GraphPad Prism (v8) was used to evaluate these findings using a Tukey and ANOVA analysis. Results: GC-MS revealed 27 components, including Eucalyptol (1,8-Cineole) (55.07%). Hemolysis recorded the greatest value, 8.16 ± 0.13. Staphylococcus aureus had the highest MIC values (1.25 mg/mL). Bacillus subtilis had a 65 mm inhibitory zone. The fungicidal effectiveness of EGEO and its major component varies according to the studied fungus strain. In terms of antioxidant characteristics, DPPH radical inhibition revealed that 1,8-Cineole has a higher IC₅₀ (4.7 ± 0.5 µg/mL). The Total Antioxidant Capacity was 22 ± 0.02 mg AAE/g. FRAP analysis showed that Eucalyptol is more potent than EGEO. Conclusion: Antimicrobial and antioxidant studies support the use of EGEO and eucalyptol in traditional and therapeutic medicine, and show their numerous possible uses as natural preservatives for perfumes and foods, as well as anticancer agents due to their hemolytic capacity. Full article

(This article belongs to the Special Issue Latest Advances in Molecular Docking Involved in Biophysics)

21 pages, 686 KB

Open AccessArticle

Functional and Transcriptional Responses of Neutrophils from Dogs Living Under Different Housing Conditions Following In Vitro Lipopolysaccharide Stimulation

by Marek Kulka, Iwona Monika Szopa, Bartłomiej Różycki and Maciej Klockiewicz

Int. J. Mol. Sci. 2026, 27(18), 8112; https://doi.org/10.3390/ijms27188112 - 11 Sep 2026

Abstract

Environmental conditions have an impact on animals’ immune systems. Neutrophils, as key components of innate immunity, rapidly respond to bacterial stimuli through the activation of inflammatory and migratory pathways. This study evaluated the transcriptional and functional responses of neutrophils derived from dogs living under different housing environments following in vitro lipopolysaccharide (LPS) stimulation. Distinct transcriptional profiles were observed among groups in genes associated with leukocyte adhesion (CD11b), chemokine signaling (CXCR1, CXCR2, and CXCL8), and cytokines (TNF-α, IL-1β, and IL-6). Additional cytokine analyses confirmed neutrophil activation and revealed differences in the magnitude and duration of cytokine secretion between groups. These findings indicate that environmental background may be associated with differences in both transcriptional responsiveness and cytokine production in canine neutrophils. Dogs originating from different housing conditions exhibited distinct patterns of inflammatory activation. The combined assessment of gene expression and cytokine secretion provides valuable insight into innate immune adaptation and might represent a useful approach for monitoring immune status in dogs. Full article

(This article belongs to the Special Issue Molecular Mechanisms of Innate Immunity and Disease Resistance in Animals)

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