Search Results (826)

Background: The overuse of traditional antimicrobial agents has accelerated the global spread of drug-resistant bacteria, posing a severe threat to global public health. Methods: In this work, a series of lipopeptides with varying fatty acid chain lengths were designed using the targeting antimicrobial peptide CL5 as the parental peptide. A variety of technical methods, including spectroscopic techniques, electron microscopy and computer simulation, were adopted to explore the self-assembly properties of the lipopeptides and their antimicrobial properties against Gram-positive and Gram-negative bacteria. Results: The results showed that lipopeptide self-assembly could be triggered by fatty acid chain modification with a carbon chain length exceeding 8 atoms, and hydrophobic interactions between fatty acid chains were the primary driving force for this process. The geometric mean of the minimum inhibitory concentrations of the lipopeptides exhibited an approximate “U”-shaped correlation with the length of the fatty acid chains. Among these lipopeptides, C8CL5–C12CL5 exhibited broad-spectrum and highly potent antimicrobial activity, with geometric means of 6.20, 5.16, and 8.00 μM against all tested bacteria, and selectivity index values of 12.26, 8.14, and 7.48, respectively. Furthermore, the lipopeptides exhibited high selectivity, rapid time-killing kinetics, as well as excellent thermal, pH and salt stability. Mechanistic studies revealed that the lipopeptides exerted antimicrobial effects through multiple pathways: disrupted bacterial cell membranes and caused the leakage of cellular contents, bound to bacterial genomic DNA, and promoted the production of reactive oxygen species. Conclusions: Collectively, lipopeptides modified with appropriate fatty acid chains exhibit broad-spectrum and highly effective antimicrobial activity, making them promising alternatives to traditional antibiotics for the treatment of bacterial infections. Full article

Accurate prediction of invasive species diffusion is essential for effective management and ecological conservation. Existing spatio-temporal Cox process models face limitations due to the separability assumption, which fails to capture spatio-temporal coupling dynamics inherent in biological diffusion processes. This study proposes a Spatio-Temporal Interaction Kernel Cox (STIK-Cox) model that constructs a non-separable conditional intensity function integrating baseline intensity, spatial and temporal proximity kernels, seasonal fluctuation, and a spatio-temporal interaction term. The model employs maximum likelihood estimation with Limited-memory Broyden–Fletcher–Goldfarb–Shanno with Bounds (L-BFGS-B) optimisation and incorporates SHapley Additive exPlanations (SHAP) for interpretability analysis. Using the Vespa mandarinia (Hymenoptera, Vespidae) monitoring dataset from Washington State, the model achieves a comprehensive accuracy score of 0.957, a capture rate of 98.74% at a 0.5° threshold, and a mean prediction error of 0.0802°. K-function analysis confirms effective capture of spatial clustering patterns, while SHAP analysis reveals longitude as the primary predictive driver. The non-separable design outperforms conventional methods including inverse distance weighting and Poisson point processes. This framework demonstrates the potential of non-separable spatio-temporal point processes for invasive species early warning, providing a scientific basis for targeted monitoring and resource allocation in ecological management. Full article

This study investigates the hydrothermal modification of commercial titanium dioxide (TiO₂) in the presence of a natural licorice root extract (Glycyrrhiza glabra L.), serving as a stabilizing and growth-modulating agent. The experimental framework combines hydrothermal treatment in a Teflon-lined autoclave with subsequent thermal calcination to elucidate the structural, morphological, and chemical evolution of the material. The plant-based extract significantly influences particle assembly during synthesis, fostering the formation of an initial organic–inorganic hybrid system that results in enhanced morphological homogeneity compared to pristine TiO₂. Thermal analyses (TGA and DSC) demonstrated the progressive decomposition of the organic components with increasing temperature, yielding a thermally stable, predominantly inorganic material at 600 °C. Scanning Electron Microscopy (SEM) observations confirmed a more uniform particle distribution in the modified samples. X-ray diffraction (XRD) patterns corroborated that the primary crystalline phase of TiO₂ remains intact across all conditions, with structural variations limited to peak definition and long-range organization. Furthermore, FTIR spectroscopy supported the preservation of characteristic TiO₂ vibrational features while indicating a gradual depletion of weakly bound surface species following thermal treatment. In conclusion, these findings demonstrate that natural extracts can effectively function as growth-modulating agents, steering material organization without altering its intrinsic chemical properties. This approach aligns with the principles of Green Chemistry and the circular economy, highlighting the potential of renewable plant-based resources as functional additives for the sustainable processing of inorganic materials. Rather than seeking to outperform commercial benchmarks, this work establishes a viable and low-environmental-impact strategy for morphological and structural modulation. Full article

Atmospheric arsenic (As) poses significant health threats in heavily polluted urban environments. However, the size-resolved distribution of water-soluble arsenic (WSAs) in atmospheric particulate matter, as well as the size-dependent variation in As concentration and solubility under contrasting haze and non-haze conditions, remains insufficiently characterized. This study investigated the concentration, size distribution, water solubility, sources, and health risks of particulate-bound As and WSAs in Beijing from April 2014 to February 2015. The annual mean PM_0.1–18 concentration was 136.96 ± 54.21 μg·m⁻³, with significantly higher levels observed during haze episodes (179.61 ± 41.71 μg·m⁻³) compared to non-haze periods (118.00 ± 49.42 μg·m⁻³). The annual mean concentration of As was 6.42 ± 3.69 ng·m⁻³, exceeding both WHO guidelines and Chinese standards during haze periods, while WSAs averaged 4.54 ± 2.50 ng·m⁻³. Distinct size distribution patterns were observed: As displayed, a unimodal fine-mode peak (0.32–0.56 μm) was observed during haze periods and a bimodal distribution during non-haze conditions, whereas WSAs followed comparable size-dependent behavior, reflecting shifts in dominant emission sources and atmospheric processes. The average WSAs/As ratio (0.72 ± 0.07) indicated high As solubility and strong associations with secondary species and anthropogenic emissions. Size-resolved analysis revealed that As was preferentially enriched in fine particles, particularly during haze episodes, whereas coarse particles became more prominent under non-haze conditions, especially in spring, likely driven by regional dust transport and its interactions with anthropogenic emissions. Deposition modeling based on the ICRP framework showed that As and WSAs were primarily deposited in the headway (HA: 0.68 and 0.32 ng·h⁻¹, respectively), followed by the alveolar region (AR: 0.29 and 0.20 ng·h⁻¹, respectively). Fine particles enhanced deposition in deeper lung regions during haze episodes, whereas coarse particles contributed more to upper airway deposition under non-haze conditions. Although inhalation carcinogenic risks remained within acceptable limits (10⁻⁶–10⁻⁴), risks were 1.60 times higher during haze periods, with adults bearing the greatest exposure burden. These findings demonstrate that haze conditions substantially alter the size distribution, solubility, and health risks of atmospheric arsenic, and provide a scientific basis for developing size-resolved and haze-targeted heavy metal monitoring strategies in urban environments subject to significant anthropogenic pollution. Full article

Oxidative stress (OS) is elevated in patients with end-stage kidney disease undergoing maintenance dialysis and contributes to increased cardiovascular risk. While kidney dysfunction and dialysis can generate OS, the acute effects of a single dialysis session remain unclear due to variability in study design and the biomarkers used. In this observational study, blood samples from 68 hemodialysis patients were collected before and after a single session. Plasma levels of the reactive oxygen species marker superoxide (O₂^•−) and OS-damage marker lipid hydroperoxides (LOOHs), protein-bound malondialdehyde (PrMDA), protein-bound thiobarbituric acid reactive substances (PrTBARSs), and protein carbonyls (PrCOs) were measured. LOOHs increased significantly by 50% post-dialysis, whereas PrMDA and PrTBARSs decreased modestly by ~10%. No significant changes were observed in O₂^•− or PrCOs. Dialysis vintage correlated positively with LOOHs, PrMDA, and PrTBARSs, but not with O₂^•− or PrCOs. No significant associations were found between OS markers and comorbidities, medication or sex. The post-dialysis rise in LOOHs, an early-formed and least accumulating lipid peroxidation marker, may reflect acute changes in OS during a single HD session. The rising association of PrMDA and PrTBARSs with dialysis vintage may suggest cumulative OS over time. Full article

Metal homeostasis, which coordinates the influx and efflux of essential elements such as iron (Fe) and manganese (Mn) in chloroplasts, is essential for optimum photosynthesis, especially in metal-accumulating plants. Brassica juncea (Indian mustard) is a metal-tolerant species with a strong metal accumulation capacity, making it a suitable model for studying transition metal homeostasis. In this study, we identified two efflux transporters, BjYSL6.1 and BjYSL6.4, that localize in the endomembrane system of Schizosaccharomyces pombe and interact with the chloroplast Mn influx transporter BjNRAMP4.1 at the plasma membrane and within the chloroplasts. Bimolecular fluorescence complementation and split-ubiquitin yeast two-hybrid assays confirmed specific protein–protein interactions among these transporters, as well as with the membrane-bound thioredoxin BjHCF164, a known regulator of photosynthetic electron transport. Gene expression studies revealed that BjNRAMP4.1 and BjYSL6 isoforms are inversely regulated under Fe and Mn stress conditions, with BjNRAMP4.1 being strongly induced under deficiency, whereas BjYSL6.1 and BjYSL6.4 are downregulated. These findings suggest that a coordinated network involving BjNRAMP4.1, BjYSL6s, and BjHCF164 modulates metal influx and efflux at the chloroplast and plasma membrane interfaces, thereby maintaining metal homeostasis, which is critical for photosynthetic efficiency in B. juncea. Full article

Holly (Ilex L.) is a genus of woody dioecious plants with substantial ecological and economic value. However, its high species diversity and morphological similarity make accurate identification challenging. To address this, we constructed a multi-taxon Ilex leaf image dataset. We then trained six deep learning models—GoogLeNet, ResNet50, ResNet101, DenseNet121, DenseNet169, and EfficientNet-B3—using a unified PyTorch framework on cloud computing resources. Leaf images were preprocessed by background removal, resizing, cropping, and normalization. Model performance was evaluated using accuracy, F1-score, and Grad-CAM visualizations. Under an image-level data split that may overestimate generalization, all six models achieved over 99% classification accuracy on preprocessed leaf images under controlled laboratory conditions. DenseNet121 and DenseNet169 performed best, reaching 99.65% accuracy. Because images of the same leaf or same plant could appear in both training and test sets under this split, plant-level cross-validation is required to assess real-world generalizability. The reported accuracies represent an upper-bound estimate under image-level splitting. The framework offers a rapid and accurate tool for preliminary screening under controlled conditions, but its performance on raw field photographs and across different collection sites remains to be validated. Full article

Disease-specific alpha-synuclein (αsyn) strains have been linked to different synucleinopathies. Current αsyn biomarkers are limited to binary detection of pathogenic αsyn in peripheral tissue biopsies or fluids, limiting differential diagnosis. Hence, there is an urgent need for methods that allow strain-specific detection and characterization of αsyn strain architecture. Notably, luminescent conjugated oligothiophenes (LCOs) have been successfully used to detect distinct protein strain conformers in prion diseases and Alzheimer’s disease, highlighting their utility in differentiating disease-specific amyloid structures. Species-dependent differences in αsyn structure are increasingly recognized as one of the critical aspects that shape how fibrils form, propagate and interact with molecular LCO probes. Here, we evaluate the potential of the LCO h-FTAA to differentiate species-specific αsyn strains and conduct a translational investigation using peripheral cardiac tissue of a gut-first synucleinopathy rodent model. Our in vitro data demonstrate strain-specific probe–fibril interactions, reflecting a differential strain architecture and cellular micro-environment. While h-FTAA binds with comparable efficiency to mouse (mo-) and human (hu-) pre-formed fibrils (PFFs), h-FTAA exhibits markedly lower quantum yield when bound to moPFFs versus huPFFs. Spectral imaging revealed h-FTAA-moPFF binding produces blue-shifted maxima (505–550 nm), contrasting with the red-shifted maxima (545–580 nm) of huPFFs. Fluorescence lifetime imaging microscopy confirmed h-FTAA’s intrinsic sensitivity to species-dependent variations through distinct temporal fluorescence signatures (moPFFs: ~0.60–1.5 ns vs. huPFFs: ~0.65–1.0 ns). Our translational investigation showed h-FTAA binding to peripheral cardiac pathology exhibits comparable red-shifted emission, but distinct fluorescence lifetimes of h-FTAA-bound aggregates in moPFF-injected (~1.0–1.4 ns) versus huPFF-injected (~0.69–0.8 ns) rats. Interestingly, we observed distinct blue-shifted emission profiles in a few selected regions of the heart of moPFF-injected rodents, further characterized by extra-long fluorescence decay shifts (~1.5–1.9 ns), reflecting differences in both aggregate conformation and maturity in moPFF-induced compared with huPFF-induced rats. Taken together, our findings underscore the potential of LCO ligands, like h-FTAA, to enable more precise disease staging and diagnosis through peripheral biopsies, complementing existing αsyn biomarker methods. Full article

Henipaviruses (HNVs), including Nipah virus (NiV) and Hendra virus (HeV), are highly pathogenic and often lethal zoonotic viruses with broad species tropism and no approved human vaccines. The emergence of genetically divergent HNVs—including Ghana virus (GhV), Langya virus (LayV), and Mojiang virus (MojV)—emphasizes the need for broadly protective countermeasures. Here, we evaluated the antibody (Ab) responses to sequential mRNA vaccines encoding the membrane-bound attachment glycoprotein (gG) from NiV, GhV, and/or LayV in a pilot study with Indian rhesus macaques. Serum binding Ab responses were quantified by ELISA against five soluble gG antigens (NiV, HeV, GhV, LayV, MojV). Functional activity was assessed by neutralization assays using NiV, HeV, and GhV pseudoviruses, and by receptor-blocking ELISA. Sequential vaccination induced high-titer IgG binding against all five HNV gGs with increasing breadth after each dose. Pan-genus regimens elicited moderate neutralizing Ab titers against NiV, HeV, and GhV, whereas the NiV-only regimen elicited potent but narrow neutralization against NiV and HeV. Conversely, the GhV-LayV-GhV regimen elicited strong binding to GhV, LayV, and MojV gG and robust neutralization of GhV pseudovirus, but limited cross-reactivity to NiV and HeV. In this pilot study, we demonstrated that mRNA vaccination can elicit broadly reactive binding and neutralizing Ab responses across phylogenetically distant HNVs. Additionally, we show GhV pseudovirus neutralization for the first time. Collectively, these data provide a foundation for the development of next-generation pan-genus HNV vaccines capable of mitigating future HNV outbreaks. Full article

Solitary living is an evolutionarily widespread yet comparatively under-theorized social system, despite its occurrence across diverse animal taxa. Shrikes (family Laniidae) are small predatory passerines that combine raptorial behavior, strong territoriality, and predominantly solitary space use, making them a powerful model for examining the ecology and evolution of solitary living. Here, I synthesize published work on shrike behavioral ecology and explicitly link these traits to the costs and benefits of a solitary lifestyle. I argue that shrikes exemplify how solitary species can offset the absence of social buffering through cognitive innovation, finetuned habitat selection, and flexible yet tightly bounded sociality. I then compare shrike ecology to solitary mammals and reptiles, highlighting convergent patterns in resource dispersion, spatial memory, risk management, and juvenile dispersal. I further examine how anthropogenic pressures, such as habitat fragmentation, climatic instability, and urbanization, interact with solitary life histories and review evidence from management interventions in both European farmland and North American systems that demographic recovery is achievable but remains contingent on addressing broader land-use conflicts and sources of adult mortality. Finally, I outline five interconnected research priorities—spanning cognitive ecology, trophic interactions, movement ecology, genomics, and formal comparative analyses—that would move shrike research from its current observational foundation toward a more experimental, mechanistic, and phylogenetically informed programme. By reframing shrikes as a model taxon for solitary living, this review aims to integrate avian behavioral ecology into broader comparative frameworks of social organization, cognition, and resilience under global change. Full article

Phenolic compounds contribute to the color, flavor, and functionality of foods but are often degraded during conventional heat treatments, prompting interest in non-thermal techniques. Thermal methods produce heat-driven changes that are more directly interpretable, whereas non-thermal methods require compound-resolved interpretation because higher post-treatment signals may reflect release from bound pools rather than true preservation. This review evaluates liquid chromatography–mass spectrometry (LC–MS) evidence on how ultrasound, high-pressure processing, pulsed electric fields, and cold plasma reshape polyphenol fingerprints across food matrices (2021–early 2026). Ultrasound and high-pressure processing preserve constitutive structures while increasing measurable phenolics through cell disruption and bound-pool release. Pulsed electric fields show similar release behavior but may shift toward oxidative losses when electroporation increases enzyme contact or downstream operations amplify degradation. Cold plasma introduces reactive oxygen and nitrogen species, with the clearest LC–MS/MS evidence for oxidation and nitration. In fresh-cut tissues, stress responses elevate phenylpropanoid products. Bulk assays such as total phenolic content (TPC) cannot separate preservation from release or true chemical conversion alone. LC–MS offers the compound-level detail needed to understand how each non-thermal technique changes polyphenol structure and functionality across food matrices. Full article

CNN with a Residual Network-50 (ResNet-50) architecture installed on a Raspberry Pi 5 is used to detect invasive aquatic plants in this study. By using object detection, the model recognizes water hyacinth, water lettuce, and water thyme and labels and bounds them accordingly. Images are taken by hand or at predetermined times, and verified detections are saved for later use. The adjusted ResNet-50 demonstrated 80.1% precision and 44.35% recall on validation, with 86.78% validation accuracy and 86.08% test accuracy. Target species from actual samples were successfully identified by the system. Full article

Streptococcus parauberis is a major pathogen responsible for streptococcosis in both marine and freshwater fish species, causing substantial economic losses in aquaculture. The increasing prevalence of multidrug resistance has highlighted the urgent need for alternative disease control strategies. Interference with bacterial quorum sensing (QS) systems represents a promising approach. This study aimed to identify and biochemically characterize an Rgg-family transcriptional regulator and evaluate its potential as a target for quorum sensing-related regulatory interference in vitro. We hypothesized that this Rgg regulator may function as a quorum sensing-associated transcription factor capable of promoter binding and modulation by small molecules. Bioinformatic analyses were used to identify the rgg gene encoding an Rgg-family transcriptional regulator and predict its structural features. The gene was cloned, heterologously expressed, and purified. Promoter binding activity was examined using electrophoretic mobility shift assay (EMSA), and key amino acid residues were identified through site-directed mutagenesis. The inhibitory effect of the cyclic peptide cyclosporin A (CsA) on Rgg-promoter binding was further assessed. The rgg gene (864 bp) encoding a 287-amino-acid protein (34.1 kDa) was successfully identified and expressed. Purified Rgg specifically bound to its own promoter region in a concentration-dependent manner. Mutations at conserved arginine residues R12 and R15 within the helix-turn-helix DNA-binding domain abolished promoter binding activity. Furthermore, CsA disturbed Rgg-promoter binding in a dose-dependent manner. This study provides the first in vitro characterization of an Rgg-family transcriptional regulator in fish-derived S. parauberis. The findings expand current understanding of Rgg-family regulators potentially associated with quorum sensing in aquatic streptococci and provide a preliminary basis for further investigation of quorum sensing-related regulatory interference strategies for controlling streptococcal diseases in aquaculture. Full article

Coral reef ecosystems are declining rapidly due to climate change, disease, and anthropogenic stressors, driving the expansion of land-based coral propagation for reef restoration. A major bottleneck in these efforts is the manual measurement of coral recruit tissue area from microscopy images, which requires 2–7 min per image and limits scalability. We present a hierarchical deep learning pipeline that automates this measurement by integrating YOLO-based detection with Segment Anything Model (SAM) segmentation. YOLO localizes recruits and classifies them by developmental stage; stage-specific fine-tuned SAM models then segment live tissue using bounding box and background point prompts to suppress segmentation leakage and improve boundary precision. Surface area is computed directly from the segmented masks using pixel size extracted from image metadata. The pipeline reduces processing time to approximately 3–5 s per image—a 24–140× speedup over manual tracing. Evaluated on 3668 microscopy images from two national coral research facilities, the system achieves a mean IoU exceeding 95% and an auto-acceptance rate (AAR) of 71.51%, where predicted-to-ground-truth area ratios fall within a ±5% tolerance of expert annotation, substantially reducing manual workload while maintaining measurement reliability across species, developmental stages, and imaging conditions. This workflow addresses a critical bottleneck in restoration research and demonstrates the broader applicability of AI-based image analysis in marine ecology. Full article

Medlar (Mespilus germanica L.) is a plant species that belongs to the Rosaceae family. Despite the nutritional and functional value of the medlar fruit, there is limited research, particularly regarding its potential as a source of dietary fibers, indigestible plant-based components, important for improving health. Fungal cellulase enzymes were used to treat medlar fruit in physiological (PRM) and consumable (CRM) maturity and obtain insoluble dietary fibers (IDF). The yield of obtained insoluble dietary fibers was 83% for both PRM and CRM. Fungal strains Aspergillus welwitschiae have proven to be significant producers of the cellulase enzyme complex and are also safe for use in food production. Swelling capacity exhibited the most pronounced response to the enzymatic treatment; 8.51–8.65% vs. 12.24–12.86% (untreated and treated fruits, respectively). Dietary fibers extracted from medlar fruits exhibited antioxidant activity that can be attributed to the presence of bound polyphenolic compounds within the fiber material. Microscopic analysis and FTIR spectra revealed structural changes in the medlar fibers due to enzyme activity, indicating partial hydrolysis of lignocellulosic components. This process enhances the functional properties of medlar-based IDF, making it a valuable ingredient for fiber-enriched food products. Full article