Search Results (2,512)

Marine-derived Streptomyces are among the most prolific producers of structurally diverse and biologically active natural products. Adaptation to unique marine environments, including deep-sea sediments, hydrothermal vents, mangrove ecosystems, marine invertebrates, and hypersaline habitats, has promoted the evolution of specialized biosynthetic systems capable of generating a broad spectrum of secondary metabolites. These metabolites include polyketides, non-ribosomal peptides (NRPs), ribosomally synthesized and post-translationally modified peptides (RiPPs), terpenoids, alkaloids, and hybrid compounds with significant antibacterial, antifungal, antiviral, antiparasitic, anti-inflammatory, and anticancer activities. Recent advances in genome sequencing, bioinformatics, genome mining, metabolomics, synthetic biology, and artificial intelligence (AI)-assisted discovery have substantially expanded marine natural product research by enabling the identification and prioritization of previously inaccessible biosynthetic gene clusters (BGCs). However, major challenges remain, including silent biosynthetic pathways, low cultivation efficiency, rediscovery of known compounds, metabolite yield instability, dereplication bottlenecks, and limited ecological interpretation. These constraints continue to impede the translation of biosynthetic potential into pharmaceutical applications. This review summarizes current strategies for marine natural product discovery and highlights emerging translational approaches integrating multi-omics technologies, pathway engineering, and AI-guided prioritization. Collectively, these advances provide a roadmap for advancing marine Streptomyces research from descriptive omics-based exploration toward experimentally validated and clinically relevant drug discovery. Full article

Background/Objectives: Endocrine resistance due to activating mutations in the estrogen receptor alpha (ERα), especially Y537S, is still a big challenge in the treatment of hormone receptor-positive breast cancer, and there is a need to develop new small-molecule inhibitors that can overcome ligand-independent receptor activation. We used an integrated machine learning and molecular dynamics (MD)-based virtual screening (VS) approach to identify potential computationally prioritized hits of ERα Y537S in this study. Methods: The dataset (~3353 compounds) was characterized using molecular fingerprints and graphically represented by PCA and t-SNE to show structurally different clusters linked to potency (pIC50). To guarantee robust downstream model training, the diagnosis of structural and influential outliers was completed through the application of rigorous data quality control methods, including the Williams plot, Mahalanobis distance, and Cook’s distance diagnostics. This was followed by multiple benchmarks of machine learning classifiers (random forest, SVM, KNN, and CNN) for activity classification, yielding the highest AUC of 0.95 for the random forest classifier. Interpretable structure–activity insights were gained by the identification of key substructures of the fingerprint by SHAP and feature importance analysis that influence the predicted potency. Three lead candidates (Hit-1, Hit-2, and Hit-3) were screened and tested with a 200 ns all-atom MD simulation in comparison with a reference control to evaluate the binding stability. Comprehensive trajectory analysis, such as PCA, FEL, RDF, salt bridges, and DCCM, was completed following the structure-based identification of the most stable ligands. Results: Three candidates were identified as Hit-1, Hit-2, and Hit-3. Hit-3 was found to be bound in the most stable binding pose and had the most similar conformational behavior to the control, whereas Hit-2 showed transient pose instability associated with increased anti-correlated domain-level motions and an alternate high-salt-bridge conformational state. As no computational metric can be an absolute measure of experimental affinity, Hit-1 has the most favorable calculated end-point binding-energy estimate, while Hit-3 showed conformational stability in MD simulations. Conclusions: The computationally prioritized candidates can be subjected to further experimental testing, as the conducted docking, MD simulations, and end-point free energy analyses cannot establish overall compound binding, cell-based activity, pharmacological mechanism, or therapeutic efficacy. Full article

As robots take on a growing role in creative work, an important question is often overlooked: how do we preserve people’s sense of psychological ownership over what they create together with a machine? This study integrates a large-scale scientometric analysis of 817 publications (2015–July 2026) with a PRISMA 2020–guided systematic review of 52 studies on Ownership-Preserving Autonomy in creative Human–Robot Interaction (HRI). Bibliometric mapping (a keyword co-occurrence network built with NetworkX and Louvain community detection, together with publication-trend, citation, author, country, and keyword temporal-intensity statistics computed directly from the corpus) shows a compound annual growth rate of approximately 26.5% over the complete calendar years 2018–2025, as well as a Core HRI and Autonomy thematic cluster that dominates a much smaller Psychological and Ownership cluster, a pattern that is at least partly attributable to the intentionally broad search strategy. The systematic review shows that only 3.8% of the 52 studies (n = 2) report a concrete algorithmic implementation coupled with robotic integration and empirical evaluation, while 96.2% do not meet this specific implementation criterion. Considered alongside converging industrial and HCI evidence on authorship erosion in AI-assisted design, as well as a previously reported ∼20% ownership decline under passive AI use in a single non-embodied creative-writing study, these SLR findings point to a pronounced theory–practice gap: rich conceptual discussion of ownership, agency, and Diminished Creative Agency contrasts sharply with the scarcity of technical implementations, validated evaluation frameworks, and real-world deployments. To help bridge this gap, the paper offers an exploratory positioning of Ownership–Autonomy Adaptive Collaboration (OAAC), a preliminary four-layer conceptual reference model; a set of falsifiable research hypotheses; and a structured research agenda on dynamic scaffolding, negotiated autonomy, and multidimensional evaluation intended to guide future ownership-preserving, human-centric co-creativity research in Industry 5.0. Full article

Commercial aromatic herbs sold under the names thyme and oregano may encompass heterogeneous plant materials, making chemical-profile screening important even when botanical identity is unknown. This study characterized 110 commercial products marketed in Türkiye and evaluated whether portable near-infrared (NIR) spectroscopy could predict chemical-profile classes derived independently from GC-FID/MS data. Commercial labels were recorded but were not treated as verified species identities. Essential oils were measured in technical duplicate for 23 volatile compounds; replicate means were subjected to compositional data treatment, principal component analysis and Ward clustering. Two clusters were selected by the silhouette criterion (0.485), and cluster stability under technical-replicate resampling was high (median adjusted Rand index, 0.907). Cluster 1 (n = 17) was relatively enriched in sabinene, caryophyllene, carvacrol and delta-3-carene, whereas Cluster 2 (n = 93) showed higher myrcene, p-cymene, alpha-pinene and beta-pinene. Two NIR spectra were collected per sample. To prevent replicate leakage, spectra were averaged before repeated nested cross-validation; a grouped-replicate analysis was also performed. A majority-class baseline achieved 84.55% accuracy but only 0.500 balanced accuracy. The best primary model, shrinkage linear discriminant analysis, yielded a mean accuracy of 0.689, a balanced accuracy of 0.565, a macro-F1 of 0.530 and a Matthews correlation coefficient of 0.103. The grouped-replicate sensitivity analysis gave a balanced accuracy of 0.592. Thus, GC-FID/MS revealed a stable chemical-profile structure, but portable NIR did not reliably recover the minority chemical class. NIR may support exploratory triage after broader calibration, but the present data do not support stand-alone botanical authentication or definitive chemical-class assignment. Full article

From a social–ecological systems perspective, cold-region rural human settlements are human-centered spatial settings adapting to population shrinkage, declining density, and prolonged cold; existing assessments often compress change into single-period scores or endpoints and mix pressures with settlement states, obscuring evolutionary pathways and transformation needs. This study examines 13 prefecture-level units in Heilongjiang, China, from 2014 to 2024 by measuring settlement state, identifying multidimensional trajectories, interpreting their pressure contexts, and deriving differentiated transformation modes. Fifteen indicators measure livelihoods and production, social equity and public services, ecological conditions, and governance response; population shrinkage, density decline, and compound cold exposure are analyzed as structural pressure contexts. Fixed-boundary normalization, Theil–Sen trend estimation, dimensional imbalance measurement, and Ward clustering are combined to identify system trajectories. The settlement state index increased from 0.301 to 0.529 (Δ = 0.229), and all 13 units ended above their 2014 levels. However, improvement was asynchronous: after fluctuating gains, the ecological dimension returned to slightly below its baseline, indicating that ecological improvement had not been consolidated. Three pathways were identified: low-level catch-up with widening imbalance, medium-level steady improvement with structural lock-in, and high-level acceleration with convergence under pressure. They correspond, respectively, to livelihood–governance reinforcement and service network adaptation, governance upgrading with ecological–livelihood coordination, and resilience consolidation under ecological constraints. Within the complete Heilongjiang prefecture system, linking measured state pathways to pressure contexts and transformation priorities provides a transparent basis for shifting cold-region rural governance from uniform expansion toward differentiated optimization of existing assets and services, while wider transfer requires indicator recalibration and multiscale outcome validation. Full article

The tripeptide glutathione (GSH) is the primary and most abundant non-protein thiol compound present in all aerobic organisms. The main function of this molecule is cellular antioxidant defense. For the first time in ciliates, using the eukaryotic microorganism Tetrahymena thermophila as a model organism, several parameters (cell mortality, molecules containing −SH groups, and total glutathione) have been evaluated under the toxic effects of various chemical stressors (including several metals/metalloids), either in combination with or without the inhibitory effects of BSO (a GSH biosynthesis inhibitor) or NEM (an inhibitor of molecules containing −SH groups). Oxidative stress caused by many of these stressors is mitigated jointly by GSH and molecules containing −SH groups (such as metallothioneins). Likewise, it requires the over-expression of GR (glutathione reductase) and GCL (glutamate cysteine ligase) genes. Bioinformatic and phylogenetic analysis of these enzymes, involved in the reduction in oxidized glutathione and in its biosynthesis, confirms their correct identification, evolutionary conservation and clustering with the taxonomic group of the ciliate species to which they belong. Full article

Sclerotinia sclerotiorum is a notoriously destructive, broad-host-range necrotrophic fungus responsible for devastating crop losses worldwide. Although genes encoding oxygenases are ubiquitous in fungal genomes, and the encoded enzymes play instrumental roles in driving diverse biochemical cascades, their specific functional repertoire in S. sclerotiorum pathogenesis remains poorly defined. Here, we characterize a contiguous pair of early-infection-induced oxygenase genes: SsOxy1 (encoding a 2-oxoglutarate-dependent oxygenase) and SsOxy2 (encoding a non-heme iron-dependent oxygenase). Targeted gene disruption demonstrated distinct developmental roles: ΔSsOxy1 mutants exhibited compromised vegetative growth (colony diameter reduced by approximately 18% to 27% at 24 h) and significantly diminished sclerotial biomass (ranging from approximately 8% to 28% reduction), whereas the absence of SsOxy2 selectively uncoupled the spatial regulation of sclerotial biogenesis without restricting radial growth. Importantly, both mutants displayed a severe decline in virulence across multiple hosts, with lesion diameters reduced by approximately 30% to 67% in ΔSsOxy1 and 62% to 66% in ΔSsOxy2 (p < 0.01).This attenuation was fundamentally linked to their inability to elaborate mature infection cushions, compounded by hypersensitivity to exogenous oxidative (H₂O₂) and hyperosmotic (NaCl) stresses. Untargeted metabolomics uncovered a profound metabolic reprogramming shared by both mutants, characterized by severe depletion of purine metabolism intermediates, including hypoxanthine (4.6–4.9-fold), xanthine (6.1–8.1-fold), and guanine (2.5–3.7-fold), alongside a disrupted glutathione redox pool (elevated GSSG: 3.0-fold in ΔSsOxy1 and 5.7-fold in ΔSsOxy2). Genomic colocalization combined with these metabolomic shifts suggests that SsOxy1 and SsOxy2 may function in a coordinated manner within a putative secondary metabolite biosynthetic gene cluster, although direct evidence for co-transcription and a shared product is currently lacking. Our findings provide novel mechanistic insights into how these paired oxygenases govern redox homeostasis, energy allocation, and the critical morphological transitions required for successful host colonization in S. sclerotiorum. Full article

Point-wise intensification of daily rainfall extremes over India is well established, yet whether their joint spatial behavior is also changing has not been tested. We address this with 75 years (1951–2025) of 0.25° gridded India Meteorological Department daily rainfall, quantifying June–September (JJAS) extremal dependence through the extremal-coefficient function θ(h) and the dependence range ρ of a Brown–Resnick curve fitted to F-madogram estimates on rank-transformed fields; the rank transform strips out marginal trends, so any surviving signal belongs to the joint structure. The all-India range over the full record is 65.6 km (95% CI 62.0–69.5 km). Across 21 sliding 15-year windows, θ at 50 and 100 km fell significantly (p = 0.033 and 0.010 after serial-correlation correction): extremes co-occur more strongly at the storm scale. The signal is regional: Peninsular India’s dependence range grew from 56 km to 76 km between the 1951–1975 and 2001–2025 blocks, a 36% expansion (p = 0.002), and Central India’s window trend is +1.7 km decade⁻¹ (p = 0.017). Independently, the largest connected daily exceedance cluster expanded in area by roughly 40% (p ≤ 0.0006). A Pettitt test dates the step in the footprint series to 1986 (p ≤ 0.0001), whereas the dependence series show progressive trends without a detectable break. Spatial reorganization is compounding marginal intensification: across Peninsular India, joint flood risk is growing faster than cell-wise return levels indicate. Full article

The structural, processing, and mechanical response of a multiphase poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)/poly(butylene adipate-co-terephthalate) (PBAT)/thermoplastic starch (TPS) matrix to two distinct glass fillers was investigated. Glass fibers and hollow glass spheres were incorporated by melt compounding and injection molding, while the unfilled blend served as the reference. Differential scanning calorimetry, X-ray diffraction, melt-flow-rate measurements, helium pycnometry, scanning electron microscopy with deep-learning-based segmentation, tensile, and Charpy impact tests were applied. At higher filler contents, the composite-level XRD-based crystallinity index decreased to approximately 47%, whereas the Scherrer-derived PHBV (110) coherent-domain size remained within approximately 21–24 nm. Preferred orientation, assessed independently from the PHBV reflection-intensity ratio, varied with filler type and content. Glass fibers progressively reduced melt flow and were associated with an increase in tensile modulus from 2.06 to 3.45 GPa and maximum tensile stress from 23.46 to 27.32 MPa at the highest investigated fiber content. Hollow glass spheres produced a non-monotonic melt-flow response, while the reduction in tensile performance at higher contents coincided with decreasing interparticle spacing and increasing specific external polymer–glass interfacial area. Within the analyzed SEM fields, no pronounced filler-rich clustering was evident. Notched specimens remained brittle, whereas unnotched specimens retained impact strength above 10 kJ × m⁻². Overall, the two filler geometries exhibited distinct relationships among apparent melt flowability, crystalline organization, quantitative microstructural descriptors, and mechanical response. Full article

Phosphonates in the ocean can serve as an alternative phosphorus (P) source for microorganisms when phosphate is scarce. Dinoflagellates cannot utilize phosphonates, but some associated bacteria can degrade these compounds and release phosphate. However, the community composition of these bacteria and their phosphonate degradation pathways remain poorly understood. In this study, the dinoflagellate Amphidinium carterae was cultured with 2-aminoethylphosphonic acid (2-AEP) as the exclusive P source. Metagenomic and genomic analyses were conducted to identify bacterial taxa and genes related to phosphonate utilization (phn genes). Specific strains were isolated from 2-AEP cultures to characterize phosphonate degradation gene clusters. Ten of the 20 most abundant genera were found to possess the genetic potential for phosphonate utilization, with Labrenzia, Phycocomes, and Pseudosulfitobacter as the dominant genera. The identified phn genes constituted multiple pathways, including the C-P lyase, PhnW-PhnX, and PhnW-PhnY-PhnA pathways, indicating that A. carterae-associated bacteria can utilize phosphonates through diverse mechanisms, with some strains even possessing more than one pathway. Five isolated bacterial strains were confirmed to be capable of degrading 2-AEP. These findings underscore the ecological significance of bacterial diversity and metabolic versatility in helping dinoflagellate hosts adapt to P scarcity, providing novel insights into bacteria-algae interactions and marine P cycling. Full article

Heterobasidion annosum is a destructive root- and butt-rot pathogen of coniferous forests, and its detection before the development of visible disease symptoms remains challenging. In this study, volatile organic compounds (VOCs) in the headspace of H. annosum-colonized Scots pine wood and fungal cultures were characterized by headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS) and compared with uncolonized pine wood and uninoculated culture medium. A total of 101 VOC signals were detected, and 98 received putative or tentative assignments. The colonized wood profile was the most diverse and comprised 64 signals, compared with 24 in uncolonized wood, 27 in the fungal culture, and 25 in the culture medium. Principal component analysis and hierarchical clustering of centered log-ratio-transformed replicate-level profiles revealed distinct compositional patterns among the four sample types. Global false-discovery-rate-adjusted q-values were below 0.05 for methyl 2-furoate, iso-longifolene, and 2-(2-furanyl)-1-propanol in the exploratory wood-profile contrast; the corresponding values for 2-methylfuran and $\beta$-barbatene were 0.0885 and 0.320. The study provides a preliminary multicomponent relative VOC profile for broader experimental and field validation. Full article

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, largely due to delayed diagnosis. Current screening approaches are limited by invasiveness, cost, and low patient adherence, underscoring the urgent need for non-invasive biomarkers that could complement the existing strategies. Cancer-associated metabolic reprogramming, together with alterations in host–microbiota interactions, is reflected in the urinary volatilome, offering a potential source of candidate biomarkers. In this exploratory, case–control pilot study, urinary volatile organic metabolites (VOMs) were profiled in patients with colorectal cancer (CRC, n = 19) and healthy controls (HCs, n = 17) using headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS). Univariate and multivariate statistical modelling was applied to characterize disease-associated metabolic patterns. Sixty-seven urinary VOMs were identified, with terpenoids, ketones, phenolic compounds and norisoprenoids representing the predominant chemical classes. Following participant-level analysis and correction for multiple comparisons, 18 VOMs remained statistically significant between the two groups, consistent with metabolic perturbations previously associated with colorectal carcinogenesis, including gut microbial dysbiosis, oxidative stress, lipid peroxidation, chronic inflammation and altered energy metabolism. Orthogonal partial least squares-discriminant analysis (OPLS-DA), validated with participant-level cross-validation and 1000 permutations, revealed a separation between CRC and HC groups, supporting the existence of a disease-associated urinary volatilomic profile. Notably, one participant initially classified as an HC was subsequently diagnosed with metastatic CRC. This participant clustered with the CRC group in an unsupervised analysis performed using the original group label, without knowledge of the later diagnosis, raising the hypothesis, to be confirmed in a prospective cohort, that urinary volatilomic alterations may be detectable before clinical diagnosis. Our findings indicate that urinary volatilomic profiling captures metabolic changes associated with CRC and represents a promising, hypothesis-generating starting point for non-invasive biomarker discovery. Full article

Background: Psoralea corylifolia is a widely used traditional medicinal plant, with its dried mature fruits as the main medicinal part. Flavonoids and coumarins are the primary bioactive compounds of this species. However, the tissue-specific metabolic profiles, gene expression patterns, and potential regulatory factors underlying active compound biosynthesis remain largely uncharacterized across different tissues of P. corylifolia; Methods: In this study, five tissue types (roots, stems, leaves, flowers and fruits) of P. corylifolia were collected as experimental materials. We performed integrated widely targeted metabolomic and transcriptomic analysis, combined with weighted gene co-expression network analysis (WGCNA), to screen co-expression modules and candidate regulatory factors associated with flavonoid and coumarin accumulation; Results: Distinct tissue specificity was observed at both metabolomic and transcriptomic levels among different tissues, with the most remarkable difference between fruits and other tissues. Signature bioactive compounds including isobavachalcone, bavachin and corylin were specifically and highly accumulated in fruits. Differentially expressed genes were mainly enriched in phenylpropanoid biosynthesis, flavonoid biosynthesis and isoflavonoid biosynthesis pathways. WGCNA revealed that the magenta module was significantly positively correlated with fruit tissues and the contents of the above bioactive metabolites. Six candidate transcription factors were identified from this module and classified into three candidate-priority tiers based on a TF–pathway gene co-expression network (344 edges, |r| ≥ 0.8, p < 0.05) and connectivity metrics. The prioritized hubs were Cluster_22013.0 (C3H-type zinc finger transcription factor) and Cluster_21217.8 (NF-YA; Arabidopsis homolog NFYA9/AT3G20910), with Cluster_9299.0 (Rcd1-like) and Cluster_20910.0 (NAC; Arabidopsis homolog NAC002/AT5G04410) as highly connected positively correlated candidates, while Cluster_31326.1 (bZIP) and Cluster_11436.0 (C2H2) were identified as negatively correlated candidates, with all their significant edges representing negative correlations with pathway genes; Conclusions: This study characterizes tissue-specific metabolic and transcriptomic patterns in P. corylifolia, and identifies candidate co-expression modules and transcription factors associated with flavonoid and coumarin accumulation in fruits. The prioritized TF tiers, including candidate hub and negatively correlated TFs, provide a foundation for future functional studies on the regulation of active compound biosynthesis in P. corylifolia. Full article

Generalized category discovery (GCD) aims to classify known categories while discovering novel ones in unlabeled data, yet existing methods lack mechanisms to correct boundary-ambiguous samples that receive noisy pseudo-labels, as they primarily rely on visual feature learning without external semantic guidance. Vision-language models (VLMs) offer a natural source of cross-modal semantic correction. However, applying VLM-guided contrastive signals directly within the GCD training loop proves counterproductive because the locally-oriented InfoNCE loss conflicts geometrically with the globally oriented K-means objective in the shared backbone space. We identify the root cause as a dual resource allocation problem: the VLM-derived signal must be allocated to the correct feature subspace to avoid geometric conflict with K-means clustering (space allocation), and the limited VLM inference budget must be allocated to the correct samples to maximize discriminative return (budget allocation). These two decisions are coupled; failure on either renders the other ineffective. To resolve this, we propose DualGLEAN, a framework that addresses the dual allocation challenge through two coupled mechanisms: decoupled contrastive alignment (DCA), which routes the VLM-guided neighbor contrastive loss to a dedicated projector space while preserving the backbone space for global clustering, and compound uncertainty querying (CUQ), a three-stage filtering metric that jointly evaluates predictive entropy, boundary proximity, and local label inconsistency to direct VLM queries exclusively to truly boundary-critical samples. Extensive experiments on the AID and RSSDIVCS datasets demonstrate that DualGLEAN achieves strong performance, improves four diverse GCD baselines as a plug-in module, generalizes across seven VLM backbones, introduces zero additional trainable parameters to the base GCD network, and incurs a total VLM API cost of only CNY 2.45 per full training run on the AID dataset under the default search-scope configuration, with the cost scaling linearly with the query budget. Full article

The widespread presence of microplastics (MPs) and associated plastic-derived compounds, bisphenols (BPs), in the environment—originating from plastic production or adsorption of environmental pollutants—results in unavoidable human exposure. Therefore, assessing their occurrence in human biological samples is essential for understanding potential health risks. In this study, pyrolysis gas chromatography–mass spectrometry was used to analyse human intraocular fluids—aqueous humour (AH) and vitreous humour (VH)—to identify 11 microplastic polymer clusters. A method based on dansyl chloride derivatisation combined with ultra-performance liquid chromatography–tandem mass spectrometry was employed to screen for five bisphenols (BPs) in blood serum collected from the same patients. Potential MPs isolated from ocular samples were qualitatively assessed by stereomicroscopy. The number of particles ranged from 14 to 69 per gram in AH and from 21 to 34 per gram in VH. Among AH samples, the most frequently detected polymer clusters were C-PVC, C-PMMA, C-PET, and C-PP, with average levels ranging from 0.41 to 0.84 µg/g. The three VH samples contained only C-PMMA, with an average concentration of 0.55 ± 0.12 µg/g. Polymers such as C-PA66 (0.30 ± 0.21 µg/g) and C-PA6 (0.15 ± 0.44 µg/g) were occasionally observed in AH. Analysis of 13 human serum samples demonstrated exposure to bisphenol A (BPA; 4.05–5.18 ng/mL) and bisphenol AF (BPAF; 2.13–4.54 ng/mL), but no clear correlation was observed between serum BP levels and intraocular MPs within the limitations of the present dataset. These findings suggest the presence of MPs and BPs in human biological samples; however, the results should be interpreted with caution owing to potential background contamination and the pilot nature of the study. Full article