Search Results (470)

Microbial degradation of phthalate esters (PAEs) is regarded as a highly promising green remediation strategy for PAE-contamination, but it still remains constrained by the scarcity of efficient microbial resources capable of degrading PAEs completely under complex conditions. This study systematically explored microbial resources resistant to dimethyl phthalate (DMP)/dibutyl phthalate (DBP) stress along with the putative degradation mechanisms in recycled plastic sewage treatment plants through high-throughput sequencing, DMP/DBP-degrading bacteria screening, and whole-genome sequencing of representative efficient DBP-degrading strains. High-throughput sequencing result revealed substantial enrichment of PAEs-degrading bacteria in activated sludge exposed to 500 mg L⁻¹ DMP/DBP. Further analysis demonstrated that the recycled plastic sewage treatment plant harbored rich culturable DMP/DBP-degrading bacteria, comprising 19 genera and 27 species of DMP-degrading bacteria, as well as 11 genera and 20 species of DBP-degrading bacteria. Notably, strain SWLYDMP 33, a potential novel species, along with 11 genera such as Paenirhodobacter, Ciceribacter, and Neorhizobium has been scarcely reported in association with PAEs degradation. Given its affiliation with a dominant genus and its superior broad-spectrum degradation performance, the representative efficient DBP-degrading strain SWLYDBP 51 was selected for whole-genome sequencing. Genome annotation of strain SWLYDBP 51 uncovered a wealth of functional genes implicated in DBP metabolism, and the putative complicated DBP degradation pathways were reconstructed, suggesting that SWLYDBP 51 might possess the genetic capacity for effectively degrading DBP under diverse environmental conditions. Overall, this study provided abundant efficient microbial resources and a theoretical reference for the bioremediation of PAEs contamination. Full article

The purpose of the present study was to investigate how periodontitis and diabetes mellitus (DM) are associated with Alzheimer’s disease (AD) through microRNA (miRNA) using AD model mice. The experimental period was 8 weeks. Twenty-four male knock-in mice (B6-AppNL-G-F/NL-G-F/J) were divided into four groups: control group fed a normal diet (C), DM group fed a high-fat/sucrose diet (DM), periodontitis (P) group, and DM + periodontitis (DM+P) group. Memory performance was compared using the Y-maze test. Next-generation sequencing was performed on brain samples, and fold changes in miRNA expression were calculated by comparing the DM+P and C groups. Integrated miRNA–mRNA analysis identified putative miRNA-targeted mRNAs, and protein expression of the top candidate gene was assessed. Memory function in the DM+P group was significantly lower than in the C group. Among the seven mRNAs identified by the integrated analysis, Neurod1 showed the greatest decrease in expression, and it was predicted to be regulated by miR-693-3p. Neurod1 protein expression in the hippocampus was significantly lower in the DM+P group than the C group. Our results suggest that the combined exposure to periodontitis and DM was associated with AD-like pathological changes and identified the miR-693-3p/Neurod1 pair as a candidate regulatory axis. Full article

Dynamic Movement Primitives (DMPs) are widely used for robot skill reproduction from demonstrations, but pose trajectory reproduction for continuous manipulation tasks remains challenging because translational and rotational motions must be represented consistently while maintaining accuracy, disturbance recovery, and terminal smoothness. Existing screw-displacement pose DMPs provide a geometrically consistent formulation on SE(3); however, their isotropic fixed-gain feedback limits direction-dependent correction, and deterministic forcing terms do not provide an explicit estimate of prediction reliability, which may cause over-shaping and high terminal jerk. This paper proposes a direction-adaptive and uncertainty-weighted pose DMP framework for robot skill reproduction from pose trajectories obtained from demonstrations. A Riemannian Motion Policy (RMP)-inspired direction-adaptive feedback mechanism is introduced to adjust recovery and damping according to the current pose error directions and magnitudes, improving trajectory-level correction and disturbance recovery. In addition, a Sparse Spectrum Gaussian Process (SSGP) is used to model the forcing term probabilistically, and its predictive variance is combined with a phase-dependent gate to attenuate low-confidence forcing contributions, particularly near the terminal phase. Simulation studies on RoboMimic trajectories show that the RMP-inspired feedback primarily improves pose reproduction accuracy and disturbance recovery, whereas the SSGP-based weighting substantially reduces terminal translational and rotational jerk, with a slight accuracy compromise relative to RMP-DMP. A papermaking robot case study further demonstrates the deployment feasibility of the generated pose trajectories on a real continuous-operation platform. Full article

Contact-rich manufacturing processes, such as surface cleaning, deburring, and polishing, require precise force regulation and complex trajectory tracking that are challenging to automate using conventional robot programming methods. Learning from Demonstration (LfD) offers a powerful alternative to transfer these expert skills from human operators to robotic systems. The objective of this study is to systematically map academic publications addressing LfD applications in robotic deburring and polishing between 2016 and 2026, classify the algorithmic structures, sensory modalities, and control configurations employed, and identify key industrial integration challenges. In accordance with the PRISMA 2020 guidelines, a systematic search was conducted across Scopus, Web of Science, IEEE Xplore, and Google Scholar databases. Out of the 288 initially retrieved records, duplicate removal and a two-stage screening process (Title/Abstract review, followed by full-text review) resulted in a final corpus of 24 primary studies included for qualitative synthesis. The included studies were classified into five algorithmic clusters: Dynamic Movement Primitives (DMPs) and variants (9 out of 24 studies, 38%), probabilistic and statistical models (8 out of 24 studies, 33%), deep learning and generative AI architectures (4 out of 24 studies, 17%), autonomous dynamical systems (2 out of 24 studies, 8%), and direct impedance control (1 out of 24 studies, 4%). Force/torque sensing remains the dominant modality; it was utilized exclusively in 71%—17 out of 24—of studies and in 87.5% of studies as any configuration (either as a sole modality or in multimodal setups). However, recent years have documented a trend toward multimodal perception and generative action policies (e.g., Diffusion Policies). The findings suggest that while LfD offers potential cost-reduction and flexibility benefits for small- and medium-sized enterprises (SMEs), technical barriers, such as the sim-to-real transfer gap, high-frequency impact dynamics in deburring, and the autonomous identification of local non-polishing areas (LNP areas), continue to limit widespread industrial deployment. Full article

Dimethyl phthalate (DMP) is an environmental contaminant known for its endocrine-disrupting properties, and its removal poses a critical environmental challenge. In this paper, we present a theoretical study of the adsorption of the DMP molecule and its isomers on pristine and nitrogen-doped graphitic surfaces, which represent the pore walls of nanoporous activated carbon, using density functional theory (DFT) calculations. Detailed wavefunction analyses were performed to elucidate the nature of adsorption on the AC surfaces. Our results reveal that nitrogen doping improves phthalate adsorption in the following order: AC-Pristine < AC-NH₂ < AC-Graphitic-N < AC-Graphitic-2N. This enhancement arises from changes in charge distribution that introduce electrostatic interactions between the COOCH₃ groups of the molecules and nitrogen-doped atoms on the AC surface. This study provides mechanistic insights into DMP adsorption on nitrogen-doped AC and offers rational guidelines for designing efficient carbon-based adsorbents for the removal of phthalate esters from contaminated water and the environment. Full article

Laccases are biotechnologically valuable enzymes that oxidize phenolic compounds across multiple industries. Their kinetic parameters Km, kcat, and redox potential (E°)—vary with substrate, origin, sequence, and structure, all of which influence electron transfer efficiency toward the trinuclear copper center. Improving kcat and E° is therefore essential for industrial applications. This review analyzes 143 studies, compiling 244 kcat values for ABTS, 125 for 2,6-dimethoxyphenol (2,6-DMP), and 53 for syringaldazine (SGZ). A high-performing laccase was defined by the upper quartile (Q3) of reported values: kcat ≥ 798, 293, and 140 s⁻¹ for ABTS, 2,6-DMP, and SGZ, respectively. Among 36 mutagenesis studies—classified as rational, semi-rational, or directed evolution—directed evolution combined with rational and semi-rational design yielded the greatest improvements, reaching kcat values up to 1328.8 s⁻¹ for ABTS. While Km data are compiled to assess catalytic efficiency, cross-study analysis reveals no consistent directional trend in substrate affinity among engineered variants. In contrast, kcat shows systematic improvement across diverse systems and substrates, establishing it as the primary performance metric for evaluating laccase engineering outcomes. Full article

Polymorphic behavior has significant consequences in solid-state properties relevant to functional materials and pharmaceutical applications. This study reports the single-crystal X-ray structure of a new third unique polymorph of the photoluminescent compound [Cu(dmp)₂](BF₄) (dmp = 2,9-dimethyl-1,10-phenanthroline). A detailed analysis of how this new polymorph compares with the two previously reported polymorphs was carried out including intramolecular metrics (τ⁴, twisting, flattening, rocking measures) and intermolecular differences (π-stacking, Hirshfeld surfaces). The new polymorph reported here has larger twisting and flattening distortions from an idealized tetrahedral geometry and the largest displacement of Cu from one dmp plane than the other polymorphs. This new polymorph also exhibits enhanced π-stacking that leads to more dense packing than previous reported polymorphs. Hirshfeld surface comparisons are consistent with a larger percentage of C…C short contacts and lower percentage of C…H contacts present in this new polymorph. The variability of intra- and intermolecular differences within this family of three polymorphs compared demonstrates the large degree of flexibility of both the coordination sphere and packing, even with the expected rigid planar bis-bidentate dmp binding to copper. As the polymorphs each show unique inter- and intramolecular features, differences in solid-state properties including solid-state photoluminescence are expected. This demonstrates the importance of phase purity in the construction of solid-state device applications. Full article

Problem statement: Contaminated mixed plastic waste—bearing metallic, paper, cardboard and organic residues—remains largely excluded from mechanical recycling because conventional routes require a costly, water- and energy-intensive washing–drying pretreatment. Research gap: No published study combines a fully dry, washing-free valorisation route for such waste with certified mechanical characterisation and a quantified CO₂ mass balance that explicitly credits elimination of the washing–drying stage. Methodology: This study presents DMP (Downcycled Mixed Plastic), a patented (OSIM, Romania) dry valorisation process based on continuous single-screw extrusion (D = 150 mm, L/D = 17.3), characterised through differential scanning calorimetry (DSC), certified mechanical/thermal testing at accredited Romanian laboratories, Weber-number dispersion analysis, and a process-parameter sensitivity study. Key findings: The composite exhibits certified mechanical properties (tensile strength 9.22 MPa, elongation at break 112.8%, compressive strength 14.5 MPa); composition–property analysis across four batches shows that increasing the PP weight fraction from 20 to 28 wt% raises tensile strength by 8.3% while reducing elongation by 5.2%; a computed Weber number (We = 166.7 ≫ We_crit) is consistent with fine PP-phase dispersion within the PE matrix; the sensitivity study confirms statistically robust structure–property relationships (R² = 0.93–0.98); and the CO₂ mass balance establishes a net avoidance of 3.150 t CO₂ eq per tonne of waste processed relative to conventional wet recycling. Significance: dry, washing-free processing is a technically promising pathway for valorising plastic waste streams currently considered non-recyclable, potentially reducing production cost by 60–70% relative to wet recycling, pending additional characterisation identified as priorities for future work. Full article

White-nose syndrome (WNS), caused by the psychrophilic fungus Pseudogymnoascus destructans, poses a severe threat to wild bat populations. Caves serve as unique microecosystems. Exploring antagonistic microorganisms and their volatile antifungal compounds within these native environments has emerged as a promising ecological control strategy. In this study, we isolated four antagonistic bacterial strains from bat cave soil that completely inhibit P. destructans. Additionally, we identified benzaldehyde (BzH) and 2,5-dimethylpyrazine (2,5-DMP) as their primary antifungal volatile organic compounds (VOCs). Combined physiological, biochemical, and multi-omics analyses revealed that these two VOCs disrupt the structural integrity of the fungal cell wall and membrane. This disruption triggers abnormal energy metabolism and compensatory ATP accumulation, leading to a significant intracellular burst of reactive oxygen species and the impairment of primary antioxidant defenses. This sustained oxidative stress causes irreversible DNA damage, endoplasmic reticulum stress, and basal metabolic dysfunction. Consequently, this cascade induces apoptosis and significantly downregulates the expression of essential virulence genes. In conclusion, this study systematically elucidates the molecular network through which VOCs released by cave soil microorganisms antagonize P. destructans. These findings provide a theoretical foundation and candidate intervention molecules for the contactless biocontrol of WNS. Full article

Background: Fear of malpractice and its potential legal, financial, and reputational consequences are associated with one of the most complex phenomena in the medical community: defensive medical practice (DMP). DMP is frequently analyzed in the specialized literature from the physician’s perspective; however, the patient’s role in triggering and maintaining defensive behaviors remains under-explored. Methods: This cross-sectional study examined contextual factors associated with fear of malpractice and the convergences between doctors’ and patients’ perspectives within a bilateral model (error–fear–perceived risk–prevention behaviors), without assuming direct causal relationship. Two questionnaires were administered in Romania to 240 dentists (March–June 2023) and 344 patients (June–December 2023). Associations were tested with chi-square and Fisher’s exact tests (reporting Cramér’s V and odds ratios), multivariate binary logistic regression, and post hoc power analysis. Results: Over half of dentists (53.3%) reported fear of malpractice despite minimal actual legal exposure (0.8%); this fear was associated with awareness of its potential consequences and perceiving patients as more demanding. In multivariate analysis, fear was the strongest independent predictor of perceiving patients as a threat (aOR = 3.98, 95% CI [1.67–9.48]). On the patient side, 57.9% would avoid a dentist with a known malpractice case and 34.0% had requested additional procedures for reassurance. Conclusions: The interaction between physician fear and patient pressure suggests the existence of a “reassurance loop”, in which the patient’s need for safety and the doctor’s fear can mutually reinforce each other, fostering defensive behaviors. We propose an exploratory typology of patient-induced DMP—direct induction (explicit requests for additional investigations/procedures) and indirect induction (relational pressure and reassurance seeking)—to guide future research. By integrating the dentist and patient perspectives within a bilateral model, the study provides a context-specific account of patient-induced defensive practice in Romanian dentistry and identifies dual-target educational interventions (addressing both clinician communication and patient health literacy) as a potential preventive direction. Full article

Horticultural intensification in Mediterranean areas has increased the risk of nitrate pollution due to inefficient irrigation and nitrogen fertilisation management. The availability of simulation models aimed at rational nitrogen management in outdoor crops is limited. The objective of this study is to adapt the VegSyst model, initially developed for greenhouse vegetables, for use in open-field conditions in relevant crops, such as processing peppers and broccoli in Extremadura. VegSyst simulates dry matter production and nitrogen uptake by incorporating the influence of evaporative demand (TUE approach) in addition to the effect of radiation (RUE approach). Experimental field data obtained in five campaigns (peppers: 2020–2022; broccoli: 2020 and 2022) under different nitrogen doses were used. The model was calibrated, and critical N dilution curves were developed for each crop. Subsequently, the simulation of fi-PAR, dry matter production (DMP) and N uptake was validated using statistical indices (RMSE, RE, d, EF) and regression analysis. The model showed a high predictive capacity for N uptake in both crops, with values of d ≥ 0.98 and EF ≥ 0.90 in the validation campaigns. The fi-PAR simulation was acceptable in peppers and excellent in broccoli. In contrast, the DMP prediction showed notable deviations in peppers, especially in 2022, attributable to interannual variations in weather conditions and physiological limitations not considered by the model. In both crops, the TUE-based strategy was a better fit for the measurements than the RUE-based strategy, indicating that under semi-arid Mediterranean conditions, transpiration is the limiting factor for biomass production. The adaptation of the VegSyst-Outdoors model proved to be robust for simulating N uptake and sufficiently accurate to be integrated into decision support tools aimed at efficient fertilisation and irrigation management. Full article

Lytic polysaccharide monooxygenases (LPMOs) are promising enzymes for lignocellulose degradation; however, wild-type LPMOs often exhibit limited catalytic activity and stability. In this study, computer-aided virtual saturation mutagenesis was applied to AnLPMO15g from Aspergillus niger, and eight potentially beneficial mutants (S197H, S197F, E185V, E185L, E185M, E185I, Q108M, and A249P) were identified based on predicted changes in unfolding free energy (∆∆G). Six mutants demonstrated enhanced activity in a 2,6-dimethoxyphenol (2,6-DMP) oxidation assay, which serves as a proxy for peroxidase-like activity. The E185V mutant exhibited a 45% increase over the wild type. The triple mutant E185V/Q108M/A249P further increased the catalytic efficiency by 56%. Notably, when combined with cellulase, E185V/Q108M/A249P enabled a 202.5% increase in reducing sugars from wheat straw, achieving a synergy degree of 1.83, highlighting its potential to improve agricultural residue conversion. Molecular dynamics simulation suggested that the E185V/Q108M/A249P triple mutant induced flexible conformational changes in six residues, which may improve substrate binding affinity. This study presents an effective strategy for engineering AA9 family LPMOs to enhance catalytic performance, facilitating efficient and cost-effective degradation of lignocellulosic biomass with implications for sustainable agricultural waste management and circular bioeconomy. Full article

Phthalic acid esters (PAEs), ubiquitous plasticizers and recognized endocrine-disrupting chemicals, pose a protracted threat to aquatic ecosystems and biodiversity. However, current ecotoxicological assessments often focus on isolated chemicals at exceedingly high laboratory doses, failing to reflect true environmental risks. This review systematically evaluates and compares the multisystemic toxicological effects of six priority PAEs (DEHP, DBP, BBP, DNOP, DEP, and DMP) using the zebrafish biological model. The synthesized evidence reveals a distinct structure–activity relationship, where long-chain and highly hydrophobic congeners exhibit substantially higher toxicity than their short-chain counterparts. Exposure to these PAEs induces severe developmental, cardiovascular, neurobehavioral, and reproductive anomalies. Specifically, DBP and BBP display the most potent cardiotoxic and neurotoxic effects, while DEHP and DBP drive profound reproductive decline and endocrine disruption at concentrations as low as 0.5–20 μg/L. Crucially, comparative environmental relevance assessments indicate that real-world PAE concentrations in industrial hotspots frequently meet or exceed these laboratory-derived lowest observed effect concentrations. These findings underscore the severe ecological risks posed by PAE contamination and position the zebrafish as a vital biological sentinel. Future ecotoxicological evaluations must prioritize chronic, low-dose mixture exposures and transgenerational toxicity to fully characterize the protracted legacy of these pollutants on zebrafish populations. Full article

Background: Plasticizers, including phthalate esters and phthalate-free alternatives, are widely detected environmental chemicals. Although increasing evidence suggests that plasticizers may disrupt gastrointestinal homeostasis, their potential molecular links with inflammatory gastrointestinal disorders (IGDs) remain unclear. Methods: This study aimed to systematically identify potential molecular targets and pathways linking representative plasticizers with IGDs. An integrative network toxicology framework was applied to investigate four plasticizers, including dimethyl phthalate (DMP), diethyl phthalate (DEP), dioctyl phthalate/di(2-ethylhexyl) phthalate (DOP/DEHP), and acetyl tributyl citrate (ATBC), in relation to Crohn’s disease (CD), ulcerative colitis (UC), esophagitis, and gastritis. Plasticizer- and disease-related targets were collected from public databases, followed by overlapping target screening, protein–protein interaction network analysis, functional enrichment analysis, GEO-based transcriptomic validation, molecular docking, molecular dynamics simulation, and single-cell RNA-seq analysis. Results: Disease-specific candidate targets were identified, including CXCL8 and FN1 for CD, IL1B for UC, MAPK3, FASN, FN1, PPARG, CXCL8, FOS, and HIF1A for esophagitis, and MMP9, TNF, TLR4, IL6, CCR2, IFNG, and PTGS2 for gastritis. Cross-disease analysis further identified plasticizer-associated signature targets, including MMP7 for DMP, HMOX1 and NOS2 for DEP, and LTF and CCL11 for ATBC. Enrichment analysis indicated that these targets were mainly involved in inflammatory, chemokine, MAPK-related, and xenobiotic response pathways. Molecular docking and dynamics simulations suggested stable interactions between selected plasticizers and candidate targets, while single-cell analysis revealed their cell-type-specific expression patterns in epithelial, immune, and stromal compartments. Conclusions: This study provides an exploratory network toxicology framework for identifying potential molecular associations between plasticizer exposure and IGDs. The findings highlight disease-specific and plasticizer-associated candidate targets that may guide future experimental validation and environmental risk assessment. Full article

Real-time deployment of modern object-detection networks on edge devices is challenging because of limited compute resources, external-memory bandwidth, and strict power constraints. To address these issues, this paper presents a host–FPGA collaborative accelerator for quantized YOLOv5n on a Xilinx Zynq-7100 platform. The proposed design includes a modular multi-operator neural processing unit supporting seven atomic operators, a Dual-Multiply Packing (DMP) scheme to improve DSP48E1-based INT8 convolution density, a cache–compute–cache dataflow with global ping-pong buffering to overlap DMA transfers and computation, and a Multi-Quantization Domain Alignment (MQDA) pipeline to preserve accuracy at Add and Cat fusion nodes. Implemented at 200 MHz, the prototype achieves 24.617 ms FPGA-side forward-inference latency, 36.686 ms end-to-end single-frame latency, 27.2 FPS system-level performance, 182.8 GOPS equivalent throughput, and 8.536 W on-chip power consumption, corresponding to 21.42 GOPS/W. Experimental results also show that INT8 quantization causes only limited accuracy degradation, while MQDA improves quantized detection accuracy by reducing cross-domain fusion error. These results demonstrate that the proposed architecture provides an effective balance among throughput, energy efficiency, hardware cost, and quantized accuracy for real-time edge object detection. Full article