Abstract: This position paper argues that recommender systems should now be designed towards agents. We use recommender systems towards agents (RSTA) to denote systems whose immediate consumer is an acting agent, an orchestration layer, or a multi-agent system; whose ranked objects are actionable interventions rather than human-viewable items; and whose success is measured by downstream trajectory utility under preference, cost, policy, and safety constraints. We advance three falsifiable claims: (1) priority-sensitive ranking can improve trajectory utility even when candidate sets are small, (2) service-side information can create value that local planning alone cannot fully recover, and (3) oversight actions such as verify, ask, defer, and escalate should be treated as recommendables rather than post-hoc filters. We sharpen the exclusion boundary against planning, routing, and human-facing recommendation; recast a WorkArena-style hardware-order task family as a full \RSTA worked example with an explicit candidate inventory, ranked intervention slate, and trajectory-level objective; and outline an agenda spanning candidate-set reconstruction, oversight-aware ranking, service-to-agent interfaces, multi-agent orchestration, interface-robust evaluation, and governance. The goal is not to relabel all agentic decision making. It is to identify a critical layer: when agents face massive action spaces or bounded compute, ranking dictates which trajectories they can reach---and which catastrophic failures they avoid.

Abstract: A broom graph is a linear graph with some pendant vertices attached to one of its ends. Using the formula for the commute time of the random walk between two vertices of the graph, which is given in terms of the effective resistance between the vertices, we find closed-form formulas for the hitting time index of some families of broom graphs, extending results found in the literature.

Abstract: Background: Climate projections for western Canada predict reduced water availability and more frequent heatwaves, underscoring the need to improve water-use efficiency and heat tolerance to sustain crop productivity and grain quality. Materials and Methods: A total of 198 historical and modern Canadian spring wheat cultivars were evaluated under water-deficient and high-temperature conditions. Measurements included whole-plant and leaf-level WUE, carbon isotope discrimination (δ¹³C) in flag leaves, and physiological traits such as leaf water potential, photosynthetically active radiation, and chlorophyll fluorescence parameters (F₀, FV/FM, FM, FV, φDo, and ETR) across six growth stages. Results: WUEWP showed a weak relationship with δ¹³C, indicating strong environmental and genetic in-fluences and limiting its reliability as a proxy across conditions. Spring wheat cultivars exhibited low genetic diversity for WUEWP and heat tolerance, suggesting limited adaptive capacity to increasing stress. Multivariate analyses (PCA and clustering) effectively captured trait variation and differentiated cultivars. Chlorophyll fluorescence traits sensitively reflected reductions in photosynthetic efficiency under drought and heat stress. Conclusion: Overall, the results indicate meaningful genotypic variation but limited genetic diversity and weak relationships among WUE, δ¹³C, and related traits, highlighting the need for new germplasm and integrated phenotyping to enhance selection efficiency and develop more climate-resilient spring wheat.

Abstract: Background: Nigeria bears a disproportionate burden of metabolic disease, with diabetes affecting an estimated 6.8-7.5% of adults and obesity prevalence among women reaching 15.7%. Despite the rich ethnobotanical tradition of using indigenous plants to manage these conditions, the molecular mechanisms by which Nigerian plant-derived phytochemicals modulate immunometabolic pathways remain poorly characterised. Objectives: This narrative review synthesises current evidence on the immunometabolic mechanisms of key phytochemicals derived from Nigerian medicinal plants, with specific focus on how these compounds regulate macrophage polarisation, inflammatory cytokine signalling, insulin sensitivity, and metabolic reprogramming in obesity and type 2 diabetes (T2D). Methods: A comprehensive narrative review was conducted using PubMed, Scopus, Google Scholar, Web of Science, and African Journals Online (AJOL). Studies reporting in vitro, in vivo, or in silico evidence for the immunometabolic activity of phytochemicals from Nigerian medicinal plants were included. Key immunometabolic targets - NF-kB, PPARgamma, AMPK, mTOR, HIF-1alpha, and macrophage M1/M2 polarisation markers - were used as mechanistic anchors for evidence synthesis. Results: Multiple phytochemicals abundant in Nigerian plants - including rutin, quercetin, luteolin, chlorogenic acid, vitexin, kolaviron, nimbolide, and 6-gingerol - demonstrate modulatory activity at immunometabolic nodes. These compounds converge on shared targets: suppression of NF-kB-driven M1 macrophage polarisation, activation of AMPK-mediated anti-inflammatory signalling, PPARgamma agonism to promote insulin sensitisation, and attenuation of HIF-1alpha-driven glycolytic reprogramming. Mechanistically, this represents a phytochemical-mediated shift from pro-inflammatory M1 immunometabolism toward an anti-inflammatory, insulin-sensitising M2 phenotype. Conclusions: Nigerian medicinal plants represent an underexplored reservoir of immunometabolic modulators. Their principal phytochemicals act on mechanistic targets directly relevant to the pathophysiology of obesity-linked T2D. Integrating ethnobotanical knowledge with network pharmacology and immunometabolic biology offers a compelling framework for rational drug discovery from Nigerian biodiversity. Future experimental validation using macrophage culture models and high-fat-diet animal systems is warranted.

Abstract: Rapid solidification by melt‑spinning produces aluminum alloys with extremely refined microstructures but also introduces strong structural gradients across the ribbon thickness. In this work, the microstructural evolution of a rapidly solidified Al‑Cu‑Li‑Mg‑Sc‑Zr alloy was investigated during model homogenization using in‑situ STEM heating experiments and correlated with bulk electrical‑resistivity measurements. The as‑cast ribbons exhibit two distinct solidification zones: a near‑contact region consisting of columnar cells containing fine Cu‑rich spherical precipitates, and a central region composed of larger eutectic cells enriched in Al₂Cu and Al₇Cu₂Fe phases. Stepwise in‑situ annealing between 200 °C and 550 °C reveals a sequence of transformations, including matrix depletion due to precipitation of strengthening phases, coarsening and dissolution of primary phases, and the formation of Al₃(Sc,Zr) dispersoids. Above 500 °C, rapid dissolution of primary phases followed by their coagulation into a limited number of stable grain‑boundary particles eliminates the original two‑zone structure and results in a fully homogenized ribbon. Ex‑situ annealing confirms that the resulting microstructure is uniform across the ribbon thickness and enables consistent precipitation strengthening during artificial aging. Microhardness measurements from both ribbon surfaces reveal identical peak‑aged hardness, validating the effectiveness of the short‑time homogenization strategy for rapidly solidified Al‑Cu‑Li‑Mg-based alloys.

Abstract: The demand for sustainable weed management and the limited discovery of new herbicide molecules have led to high interest in plant-derived bioherbicides, such as the water residues (WRs) from the hydrodistillation of aromatic plants, which contain biologically active secondary metabolites. Here, the phytotoxic potential of WRs of four aromatic plant species was investigated. Chemical composition of WRs was determined by SPME–GC–MS, and their effect was assessed on seed germination and seedling growth characteristics of Avena sterilis, Echinochloa crus-galli, and Zea mays. Five concentrations, i.e., 0, 10, 20, 50, and 100, with 100 representing pure WR were tested. Phenolic monoterpenes dominate WRs in oregano and thyme, and oxygenated monoterpenes in laurel and lavender. Germination and growth responses were dose-dependent and species-specific. Oregano and lavender WRs exhibited the strongest phytotoxicity, reducing weed germination by 82% and 79%, respectively. In contrast, laurel extracts showed weaker germination inhibition. Across all tested species, germination delays were observed, making WRs a promising candidate for weed control. The results also showed that WR affected root growth by up to 95% shoot by 70–80%. Maize exhibited greater tolerance than the weed species maintaining higher germination. Overall, WRs represent a promising tool for integrated weed management.

Abstract: Einstein's principle of the invariance of the speed of light in a vacuum is a core of modern physics, but the ISO 13690:2008 standard is only applicable to the visible light band, and traditional measurements have not verified the universality of vacuum permittivity and permeability across all bands. This study combs the limitations of historical precision measurements of the speed of light, derives the wavelength dependence of and in the interstellar medium based on quantum electrodynamics (QED) and Maxwell's equations, and proposes a micro-scale measurement scheme of "three-stage path splitting + two-dimensional compensation". Taking the 2026 Jupiter occultation as the carrier, a multi-band synchronous observation experiment is designed to predict the multi-band arrival sequence and time difference, providing theoretical and technical support for the refinement of light speed measurement and the expansion of the applicable boundary of relativity.This study provides a feasible precision metrology framework for high-accuracy light speed measurement in complex media, with potential engineering applications in astronomical observation and electromagnetic parameter calibration.

Abstract: Micro- and nanoplastics (MNPs) have now been detected in human blood, placenta, and arterial tissue, yet the oral cavity, which serves as the primary portal of environmental exposure, has received strikingly little mechanistic attention. This narrative review addresses that gap from an environmental microbiology perspective, synthesizing recent literature on periodontal disease, chronic low-grade inflammation, oral biofilms, dental materials, microbial–plastic interactions, and systemic chronic disease risk. Unlike prior reviews, we apply an explicit evidentiary framework that distinguishes what is directly demonstrated from what is biologically plausible but unproven, and we situate the periodontal environment specifically as a particle-retention and inflammatory-amplification niche. The strongest direct oral evidence shows that human dental calculus harbors at least 26 microplastic types, dominated by polyamide (41.4%), polyethylene (32.7%), and polyurethane (7.0%). Polyethylene isolated from calculus induces cytotoxicity, apoptosis, impaired migration, NF-κB activation, and upregulation of IL-1β and IL-6 in human gingival fibroblasts. The oral cavity is also a portal for environmental exposure and a local site of plastic generation: MNPs are released from chewing gum, oral care products, orthodontic appliances, and resin-based dental materials, while oral microorganisms have been documented to degrade methacrylate polymers. Across experimental systems, MNPs activate oxidative stress, inflammasome signaling, macrophage polarization, and barrier dysfunction — pathways that overlap extensively with the pathobiology of periodontitis. Environmental biofilm studies further indicate that plastic substrates can enhance extracellular polymeric substance production, quorum sensing, antibiotic resistance gene transfer, and pathogen persistence, suggesting a plausible but not yet proven oral plastisphere within plaque and calculus. We argue that periodontitis should be reconceptualized as a chronically inflamed particle-processing interface that may increase local MNP retention, cellular reactivity, and systemic inflammatory spillover, with implications for cardiovascular, metabolic, and other chronic disease risk pathways. Current evidence does not yet prove that environmental MNP exposure causes human periodontitis, and that evidentiary boundary is maintained throughout. A priority research agenda is proposed, centered on contamination-controlled subgingival biomonitoring stratified by periodontal status, spatially resolved multi-species biofilm models, polymer source attribution, and longitudinal clinical studies linking oral plastic burden to inflammatory and systemic outcomes.

Abstract: Contrastive learning–based models such as DrugCLIP have recently emerged as scalable tools for structure-based virtual screening by embedding protein structures and small molecules into a shared representation space. While these approaches demonstrate high throughput and competitive screening performance in ligand retrieval tasks, their ability to correctly identify biologically relevant ligand-binding pockets has not been systematically evaluated. Here, we construct a benchmarking dataset comprising 42 pharmacologically diverse human protein targets with experimentally validated drug-bound structures spanning multiple target families. Using this dataset, we evaluate the pocket recognition capability of DrugCLIP and compare its performance with a traditional structure-based workflow that integrates geometric pocket detection (Fpocket) with dynamics-informed pocket ranking (ESSA). DrugCLIP achieves perfect success rates for several well-studied target classes, including kinases (10/10), GPCRs (5/5), and nuclear receptors (5/5), but shows markedly reduced performance for ion channels (1/4) and transporters (2/5). Notably, pocket prediction accuracy does not strongly correlate with structural data availability, suggesting that intrinsic pocket characteristics rather than training data abundance primarily affect model performance. Across the benchmark, DrugCLIP does not outperform traditional pocket identification strategies (DrugCLIP vs. Fpocket+ESSA: 74% vs. 79%). Together, these results provide a quantitative evaluation of pocket recognition by contrastive learning–based models and highlight key limitations that should be considered when applying embedding-based approaches in prospective structure-based drug discovery.

Abstract: This paper critiques the established loss of simultaneity in special relativity which comes from Minkowski diagrams. Einstein's original thought experiment, with a train (observer M’), an embankment (observer M) and simultaneous lightnings, will become our test. For our purpose, lightnings will become photons. By applying the two postulates of special relativity (speed of light and principle of relativity), the paper shows that simultaneity should be observed by both observers. This would imply a superposition of some kind, as the photons meet simultaneously M and M’ while they are not at the same position. By using Lorentz invariance (therefore pure calculation), the conclusion of simultaneity for both observers will be confirmed. The superposition could be a quantum superposition. The conclusion is that Minkowski diagrams with their oblique coordinates are probably correct but, lacking the idea of superposition, fail to fully describe special relativity.

Abstract: One of the most promising approaches for replacing conventional power plants during the transition to clean energy is the conversion of existing coalfired power plants (CPPs) into nuclear power plants. This strategy offers numerous ecological and economic advantages. However, integrating a nuclear reactor with a steam turbine originally designed for a coal plant is far from trivial and involves significant technical challenges. The purpose of this work is to analyze and evaluate various options for coupling a HighTemperature GasCooled Small Modular Reactor (HTGR SMR) with a potentially suitable subcritical steam turbine from an existing CPP, thereby creating several repowering configurations. The main difficulties stem from the fact that the turbine was designed to operate with live steam at lower flow rates, temperatures, and pressures than those typically provided by an HTGR SMR. In addition, the feedwater temperature and pressure requirements for the HTGR SMR steam generator differ substantially from those in a CPP, leading at best to additional efficiency losses. Moreover, the overall thermal cycle layouts of the two systems are fundamentally different. Despite these challenges, technically feasible combinations can be achieved. However, determining which option is the most economically viable depends on numerous additional factors, including the specific characteristics of the individual CPP and the regulatory framework of the country in which it operates.

Abstract: Ticks are important arthropod vectors that transmit various pathogens to humans, livestock, and wildlife, thereby contributing significantly to the global burden of vector-borne diseases. The tick microbiome, consisting of bacteria, viruses, protozoa, and other microorganisms, plays a crucial role in pathogen transmission dynamics and the emergence of new zoonotic diseases. This review examines the characteristics of tick vectors, the composition and dynamics of tick-associated microbiomes, and their implications for zoonotic disease transmission. We analyze current knowledge of tick-borne pathogens, including Borrelia burgdorferi, Rickettsia species, Anaplasma species, and Coxiella species, and highlight the potential for microbiome constituents to serve as reservoirs for emerging pathogens. The complex interactions between tick hosts, their microbiomes, and vertebrate hosts create opportunities for pathogen evolution and interspecies transmission. Recent advances in molecular techniques have revealed previously unknown microbial diversity within tick populations, suggesting that many potential zoonotic pathogens remain undiscovered. We discuss future research directions, including field screening methodologies for pathogen detection, microbiome-based risk assessment approaches, and the development of novel prevention strategies, including tick vaccines.

Abstract: With the advent of the neural network era, traditional machine learning methods have increasingly been overshadowed. Nevertheless, continuing research on the role of geometry for learning in data science is crucial to envision and understand new principles behind the design of efficient machine learning. Linear classifiers are favored in certain tasks due to their reduced susceptibility to overfitting and their ability to provide interpretable decision boundaries. However, achieving both scalability and high predictive performance in linear classification remains a persistent challenge. Here, we propose a theoretical framework named geometric discriminant analysis (GDA). GDA includes the family of linear classifiers that can be expressed as a function of a centroid discriminant basis (CDB0) - the connection line between two centroids - adjusted by geometric corrections under different constraints. We demonstrate that linear discriminant analysis (LDA) is a subcase of the GDA theoretical framework, and we show its convergence to CDB0 under certain conditions. Then, based on the GDA framework, we propose an efficient linear classifier named centroid discriminant analysis (CDA) which is defined as a special case of GDA under a 2D plane geometric constraint. CDA training is initialized starting from CDB0 and involves the iterative calculation of new adjusted centroid discriminant lines whose optimal rotations on the associated 2D planes are searched via Bayesian optimization. CDA has good scalability (quadratic time complexity) which is lower than LDA and support vector machine (SVM) (cubic complexity). Results on 27 real datasets across classification tasks of standard images, medical images and chemical properties, offer empirical evidence that CDA outperforms other linear methods such as LDA, SVM and logistic regression (LR) in terms of scalability, performance and stability. Furthermore, we show that linear CDA can be generalized to nonlinear CDA via kernel method, demonstrating improvements on the linear version with tests on three challenging datasets of images and chemical data. GDA's general validity as a new theoretical framework may inspire the design of new classifiers under the definition of different geometric constraints, paving the way towards a deeper understanding of the role of geometry in learning from data.

Abstract: Glutamine is the most abundant amino acid in human plasma and tissues and plays essential roles in cellular metabolism, biosynthesis, and redox homeostasis. Beyond these canonical functions, glutamine availability and utilization have emerged as key regulators of multiple cellular stress responses, including the integrated stress response, endoplasmic reticulum stress, metabolic checkpoint signaling, and autophagy. During viral infection, host glutamine metabolism is frequently reprogrammed to meet the energetic and biosynthetic demands of viral replication, thereby inducing or reshaping glutamine-linked stress pathways. Increasing evidence indicates that these stress responses are not merely secondary consequences of infection but actively influence key stages of the viral life cycle, including viral entry, genome replication, protein synthesis, and host antiviral responses. In this review, we summarize current advances in understanding how glutamine metabolism regulates cellular stress responses in the context of both viral and non-viral infections, and how these pathways, in turn, modulate viral pathogenesis and host defense. We discuss the context-dependent roles of glutamine-linked stress signaling in either promoting viral replication or restricting infection, depending on viral species, host cell type, and metabolic conditions. Finally, we highlight emerging concepts and unresolved questions, including the potential of targeting glutamine metabolism and associated stress pathways as host-directed antiviral strategies. A deeper understanding of the interplay between glutamine metabolism, cellular stress responses, and viral infection may provide new insights into disease mechanisms and inform the development of novel therapeutic approaches.

Abstract: Residential construction is the only large-scale production system that has resisted the deflationary intelligence that reduced computation cost by a factor of ten trillion and genome-sequencing cost by fifteen million within a single generation. We argue this resistance is not coincidental: it is a structural consequence of a geometric compound of environmental distortions (D = exp(∑wₖ·ln(dₖ))) whose six channels have remained simultaneously elevated — a configuration that no single-channel intelligence intervention can overcome. We formalise distortion axiomatically, derive the geometric formula by necessity (not empirical fit), and introduce the Channel Synchronization Index (CSI) as an operational predictor of deflationary inflection: when CSI ≥ 3 channels compress simultaneously, a nonlinear phase transition in construction cost becomes likely. We calibrate a six-channel D_urban model against OECD, ILO, World Bank, and Eurostat data (2010–2026), compare current AI systems (GPT-4o, Claude 3.5/4, Gemini Ultra, agentic frameworks) by their D-compression capacity, and run a 10,000-scenario Monte Carlo simulation (Deucalion HPC, FCT Grant 2025.00020.AIVLAB.DEUCALION). Central estimate for sustained deflationary inflection: 2031–2035. Under a coordinated agentic AI scenario (CSI ≥ 5 by 2032), a 90% real price decline from peak becomes structurally achievable by 2050–2060. We provide eight falsifiability criteria. Definitions, axiom proofs, and full methodology are in the Appendix.

Abstract: Background: The negative impact of Adverse Childhood Experiences (ACEs) on child development is documented. The parent-child relationship protects against ACEs and improves healthy child development. Hence, the parent-child environment plays a crucial role in preventing and mitigating ACEs through positive childhood experiences that elicit parental resilience. However, our understanding of the parent-child relation-ship within the social-ecological model (SEM) (i.e., intra- and interpersonal, community, and societal levels) is limited. Objective: This study explores parents’ perspectives on parental resilience as a protective factor for preventing ACEs and supporting PCEs at every level of the SEM, while considering parents’ personal ACE scores and emotional regulation (ER) scores. Method: This study uses a thematic analysis approach for qualitative research. In-depth individual interviews were conducted with members of a parent support group (PSG) (82% female, n = 14) based in a community-based organi-zation serving families (n = 17 parent interviews). Demographic information, ER, and ACE scores were collected for each participant. Results: Seven themes and 16 subthemes were identified, including parents experiencing aspects of emotional regulation from joining a PSG at all SEM levels, sensing a communication disconnect with school teachers, and parents desiring ACE prevention/mitigation training. Conclusion: ‪The insights on parental resilience perceptions are valuable and hold promise to inform future multi-level prevention strategies and mitigation practices using the SEM.

Abstract: Pediatric brain tumours are highly prevalent and remain one of the leading causes of cancer-related deaths in children. There are numerous different brain tumour types that are now well characterized by magnetic resonance imaging (MRI), patient clinical course, neuropathological and molecular genetic alterations. One of the challenges with treating pediatric brain tumours with systemic chemotherapy is the inability of several chemotherapeutic agents to cross the blood brain barrier (BBB) which serves as a protective mechanism for neuronal homeostasis. The BBB is primarily comprised of microvascular endothelial tight junctions. Controlling BBB permeability to allow for therapeutics to cross and combat brain tumors is now possible using MR-guided Focused Ultrasound (MRgFUS). In this approach, microbubbles are administered intra-venously prior to MRgFUS BBB disruption at the targeted tumour site in the brain. In the presence of MRgFUS, the microbubbles in the brain capillaries oscillate, and temporarily disrupt the BBB enabling systemically administered chemotherapy drugs to cross at the targeted site. In this review, we provide evidence supporting the use of MRgFUS BBB disruption to treat brain tumours in animal models, and in on-going human clinical drug trials. We conclude with efforts to harness the potency of the immune system using MRgFUS against pediatric brain tumours.

Abstract: Minimally invasive aortic valve replacement (MIAVR) via transaxillary access, right anterior thoracotomy (RAT), and ministernotomy has matured from niche innovation to guideline-endorsed standard, yet comparative data remain heterogeneous and fragmented. Objectives: This state-of-the-art review synthesizes contemporary evidence to define the role of each approach within modern valve care pathways. A PRISMA 2020 systematic review with PROSPERO registration identified studies reporting outcomes of isolated AVR performed through transaxillary, RAT, or ministernotomy access. Primary endpoints were 30-day mortality, operative times, and length of stay; secondary endpoints included complications, long-term survival, learning curves, and patient-reported outcomes. Forty-two studies encompassing 15,328 patients were included: transaxillary (n=2,156), RAT (n=4,892), and ministernotomy (n=8,280). All approaches achieved excellent perioperative safety (mortality 0.4–2.5%) and long-term survival comparable to full sternotomy, while consistently reducing blood loss, transfusion, ventilation time, and hospital stay. Ministernotomy offered broadest anatomical applicability and the shortest learning curve (20–30 cases). RAT combined complete sternal preservation, lowest bleeding rates, and superior cosmetic and functional recovery in anatomically suitable patients. Transaxillary access provided hidden scarring and attractive options in redo or sternum-avoidance scenarios, but higher reported stroke rates (2.0–6.3%) and greater technical demands limited its use to high-volume centres. MIAVR via ministernotomy, RAT, and transaxillary access now represents a mature, durable alternative to full sternotomy. A structured, anatomy- and centre experience–driven selection strategy is essential to fully realize its benefits across diverse patient populations.

Abstract: Dementia affects approximately 55 million people worldwide, yet the psychological experience of diagnosis and the determinants of post-diagnostic wellbeing remain underexplored relative to biomedical research priorities. The existing literature has been predominantly deficit-oriented, focusing on cognitive decline, neuropsychiatric symptoms, and carer burden, with limited attention to preserved psychological capacities and what supports flourishing following diagnosis. This narrative review applies a positive psychology framework to synthesise evidence on meaning, purpose, hope, and post-diagnostic adjustment in early-stage dementia. A central empirical observation motivating the review is the wellbeing paradox: the consistent finding that subjective wellbeing in early-to-moderate dementia is frequently higher than carers and clinicians predict, and is more strongly associated with psychosocial variables than with objective cognitive status. Evidence from the IDEAL cohort and related longitudinal research demonstrates that emotional responsiveness, need satisfaction, and capacity for meaning-making are preserved in early-stage dementia and constitute clinically relevant assets. Four positive psychology constructs are identified as evidence-based targets for intervention: hope, self-compassion, social identity, and meaningful engagement. Clinical implications include the integration of strengths-based assessment, meaning-centred group interventions, structured peer support, and validated positive outcome measures into post-diagnostic care pathways. Health equity considerations and research priorities are addressed, including the underrepresentation of minority ethnic communities and people with young-onset dementia in existing research. The review argues that meaningful progress requires deliberate reorientation of clinical, commissioning, and research priorities toward a positive psychology framework for dementia care.

Abstract: The transition from fossil-based resources to renewable feedstocks is a cornerstone of industrial decarbonization. A critical component of this shift lies in deriving intermediates and value-added products from biomass. Among renewable resources, lignin stands out as a promising candidate due to its wide availability, abundance, and non-competitiveness with food production, making it an ideal starting material. The removal and depolymerization of lignin to produce aromatic chemicals can significantly enhance the material usability of all lignocellulose constituents. The removal and depolymerization of lignin to produce aromatic chemicals can significantly enhance the material usability of all lignocellulose constituents. Herein, a process for the polyoxometalate-catalyzed oxidative depolymerization of technical lignins to produce the monoaromatic compounds vanillin (Va), methyl vanillate (MeVa), syringaldehyde (Sy), and methyl syringate (MeSy) is demonstrated, offering the possibility to achive high monoaromatic yields of up to 12wt%.