Abstract: Remote sensing has become a core technology for environmental and climate monitoring, supported by expanding sensor constellations, advanced processing capabilities, and coordination frameworks established by the European Space Agency (ESA), Global Earth Observation System of Systems (GEOSS), and Committee on Earth Observation Satellites (CEOS). Ensuring consistency across missions requires robust geometric and radiometric calibration and validation. However, traditional reliance on ground control points (GCPs) is limited by sparse global coverage, temporal instability, and dependence on surveyed accuracy. While alternative geospatial datasets, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) point clouds, and vector databases, can serve as references, challenges remain in data access, automation, and cross-sensor applicability. This study proposes a generative adversarial network (GAN)–based approach to generate geometrically consistent image chips from vector maps. Two models were trained at 50 cm and 10 m resolution within the ESA-supported Generative Ground Control Point (GenCP) study, using Sentinel-2 and very-high-resolution RGB imagery. The generated GenCP image chips are evaluated using image-based similarity (radiometric consistency), geometric, and model-performance metrics. Results demonstrate their suitability for automated Cal/Val workflows and their potential as scalable, fit-for-purpose reference datasets.

Abstract: Regulation of the cell cycle is critical for maintaining genomic integrity. Therefore, cells have adapted several mechanisms to ensure that cell cycle events occur in a precise order. Some mechanisms regulate cell cycle progression by inhibiting cell cycle drivers, cyclin dependent kinases (CDKs). The Wee1/Myt1 family of kinases regulate the G2 to M phase transition by phosphorylating and inactivating Cdk1. Investigations of Wee1/Myt1 have mainly focused on its regulation of mitosis; the role of Wee1/Myt1 kinases in the meiotic cell cycle is less well understood. However, misregulation of Wee1/Myt1 during meiosis can have a range of fertility consequences from mild to severe, including human fertilization failure and infertility. Studies from several organisms reveals that the meiotic functions of Wee1/Myt1 kinases differ from mitosis depending on the species and sex. Here, we review how Wee1/Myt1 kinases regulate cell-cycle progression in meiosis across species. We highlight current knowledge of Wee1/Myt1 in meiosis and discuss unanswered questions and new directions to advance the fields of meiosis, reproduction, and development. Understanding the molecular and cellular functions of Wee1/Myt1 homologs in these various systems may contribute to the discovery of the mechanisms underlying human infertility cases, better diagnoses, and clinical treatments.

Abstract: IIce hockey represents a sport with predominantly anaerobic efforts best reflected by repeated sprint ability (RSA) testing (5x5 seconds with 10 seconds recovery). A controversy persists about the usefulness of V̇O2 max laboratory testing for the assessment of ice hockey players. The purpose of the study was to evaluate the relationship between laboratory measured V̇O2 max and RSA simulated on a supine ergometer and tested on ice. Elite male hockey players (n = 64) were tested in the laboratory (V̇O2 max and RSA). RSA was performed by modified Wingate test (5 x 5-seconds sprints with 10 seconds recovery). In 28 athletes RSA were assessed during an on-ice testing (5 maximal skating sprints between the goal and the blue line). The decrease in performance was assessed by fatigue indices. In the laboratory settings the V̇O2 max correlated significantly with maximum workloads of the 2nd, 3rd, 4th and 5th bout with increasing correlation strength (r= 0.26, p=0.02; r=0.48, p< 0.001; r=0.57, p< 0.001; and r=0.60, p< 0.001) and with fatigue indices - % workload decrement index (r = 0.44, p< 0.001) and % maximum average workload decrement (%) (r=0.38, p=0.002). In addition, V̇O2 max correlated with lactate levels after 10 minutes of recovery (r=0.31, p=0.01). There was no correlation between V̇O2 max and on-ice testing results. Moreover, the results of RSA measured in laboratory and on ice did not show any correlation. The lack of relationship between laboratory and on-ice testing is further challenging the usefulness of bicycle ergometry laboratory testing in ice hockey.

Abstract: Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by the simultaneous disruption of interconnected molecular pathways, yet the structural mechanisms underlying this transcriptional disintegration remain poorly characterized. To address this, we constructed condition-specific gene co-expression networks from DLPFC bulk RNA-seq data, using a mutual information framework with Infomap community partitioning. Functional enrichment of network communities via Ingenuity Pathway Analysis (IPA) identified GABAergic signaling, SNARE complex assembly, Synaptogenesis, and Neurexins and Neuroligins interactions as significantly overrepresented pathways. Integration of node degree with condition-specific average expression revealed coordinated topological centralization of key synaptic genes — including NRXN2, LRRTM1, DLGAP3, and SHANK1 — alongside a widespread transcriptional downregulation in GABAergic and Synaptogenesis modules. Shortest path analysis further demonstrated a consistent expansion of intra-pathway distances across all evaluated canonical pathways in AD, quantifying a progressive loss of local communication efficiency. These findings reframe LOAD as an active structural rewiring process, in which the transcriptional network consolidates remaining resources around essential synaptic components as a molecular signature of the pathological state.

Abstract: This report describes the practical implementation of a maximum power point tracking (MPPT) system for a string of four series‑connected monocrystalline silicon photovoltaic (PV) cells. The system includes a boost DC‑DC converter that interfaces the low‑voltage PV string to a 36 V battery, and each cell has an individual MOSFET bypass switch to mitigate partial shading. We explain the operating principles, the MPPT algorithms (Perturb & Observe and Incremental Conductance), the bypass logic, and the closed‑loop control that adjusts the converter’s duty cycle to maximise power transfer. Step‑by‑step descriptions and supporting figures clarify the process.

Abstract: Laser polishing (LP) is widely employed to enhance the surface quality of additively manufactured (AM) metals; however, its behaviour within deep or confined internal geometries remains insufficiently understood. Many high-performance AM components, such as biomedical implants, turbine cooling channels, and metal microfluidic systems, incorporate narrow internal features where heat-transfer conditions differ significantly from open surfaces. In this study, laser powder bed fusion (LPBF)-fabricated 316L stainless steel specimens containing ~10 mm deep slots with widths ranging from 1 to 5 mm were subjected to laser polishing using a continuous-wave fibre laser (power: 80–120 W, scan speed: 450–750 mm/s, spot size: ~80–100 µm, ~60–70% track overlap, single-pass strategy). The influence of internal geometric confinement on microstructural evolution and mechanical response was systematically investigated. A pronounced depth-dependent microhardness gradient was observed along the slot wall, with hardness decreasing from approximately 270 HV in the lower region to ~210 HV near the slot opening, with more significant gradients in narrower geometries. Quantitative grain-size analysis revealed finer grains (~8–12 µm) in the lower region and coarser grains (~18–25 µm) toward the upper region, indicating progressive grain coarsening with increasing height. These variations are attributed to geometry-dependent thermal boundary conditions, where enhanced conductive coupling to the bulk substrate in the lower region promotes higher cooling rates, while reduced thermal extraction near the slot opening results in slower solidification. The results provide clear experimental evidence that internal geometric confinement can significantly influence microstructure–property evolution during laser polishing, even under constant processing parameters. This study highlights the importance of incorporating geometric effects into post-processing strategies for AM components and offers practical insights for achieving more predictable and uniform mechanical performance in confined internal features.

Abstract: N-Methyl-D-aspartate (NMDA) receptors are ligand- and voltage-gated ion channels essential for synaptic plasticity, learning, and memory. The GluN2B subunit, highly expressed in the forebrain and spinal cord, is implicated in multiple neurological and psychiatric disorders, making it an attractive target for positron emission tomography (PET) imaging. However, the development of selective GluN2B PET radioligands remains challenging. Here, we describe the design, synthesis, and evaluation of eighteen 3-alkylaryl derivatives of 7-methoxy-2,3,4,5-tetrahydro-1H-benzo[d]azepin-1-ol, including enantiomerically resolved compounds, as candidate PET radioligands. Structure–activity relationship studies show that binding affinity is largely insensitive to electronic and steric variation at the terminal aryl group but strongly dependent on alkyl linker length, with a four-carbon chain providing optimal affinity. Binding affinity does not correlate with calculated lipophilicity, suggesting hydrophobicity is not the primary determinant of receptor interaction. Absolute configuration was established using vibrational circular dichroism and infrared spectroscopy, and docking studies provided insight into enantiomer-specific binding modes. Two ligands, L3 and L6, and their enantiomers exhibited high GluN2B affinity, favorable physicochemical properties, and suitability for carbon-11 labeling. PET imaging confirmed strong and specific brain binding of the radiolabeled compounds. These findings establish this scaffold as a promising platform for GluN2B PET ligand development.

Abstract: This study examines the microspherical high-calcium fly ash (HCFA) and the high-strength binder material based on it by method of scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS). The composition of 568 individual microspheres of the initial HCFA was determined and presented as ternary diagrams CaO–Al2O3–SiO2 and CaO–FeO–SiO2. The binder specimens have a compressive strength of 24–90 MPa at a curing time of 3–300 days. Their strength is close to that of CEM I 42.5N cement specimens with a curing time of up to 28 days, but exceeds it with a curing time of up to 300 days. The SEM-EDS method showed that the predominant composition of hydration products is concentrated in the high-calcium region of the CaO–Al2O3–SiO2 diagram with a CaO content of 60–80%. The SiO2 content in them is 15-30%, and their composition includes 1–15% Al2O3 and 5–14% FeO. The SEM-EDS method allowed us to understand the transformation of calcium silicate glass microspheres into C-S-H gel, which is the main component of the strengthening matrix. The results contribute to the data for development of models for predicting the effect of HCFA on the properties of composite binders.

Abstract: This review aims to provide comprehensive and practical information on the once-nearly-forgotten but now resurgent roles and trends of autologous transplantation in leukemias. We seek to categorize when it is necessary as a first-line treatment (plasma cell leukemia) and to identify well-defined patient subgroups (such as certain types with intermediate prognosis in AML, APL second remission, etc.) in which autologous transplantation might be comparably or even slightly more effective than allogeneic transplantation, not only in frail patients. In some leukemias, such as CLL, autologous transplantation still does not play a role. Attempts to achieve anti-leukaemic effects in autologous settings have proven largely ineffective, but new approaches might be promising. Newer cell therapies (such as CAR-T) are significantly more effective, and the same applies to in vitro graft purging. However, this area has been investigated relatively recently in an innovative manner, using specific graft pretreatments that may also stimulate anti-leukemic immune responses in autologous cases.

Abstract: This study presents the first comprehensive molecular characterization of Escherichia coli producing extended-spectrum beta-lactamases (ESBL-Ec) in surface waters in Albania, focusing on the Shkumbini river. Antimicrobial resistance (AMR) in aquatic ecosystems poses a significant threat to public health, yet data from Albania remain scarce. Thirty water samples were collected from six locations near Elbasan between September 2022 and February 2024. Following the WHO Tricycle protocol, 52 ESBL-Ec isolates were recovered and characterized for antimicrobial susceptibility, biofilm formation, resistance genotypes and clonal relatedness via pulsed-field gel electrophoresis (PFGE). ESBL-Ec was detected in 80% of the samples analyzed, with 94.2% of the isolates classified as multidrug-resistant (MDR). High resistance frequencies were observed for ampicillin (98.1%) and cefotaxime (86.5%), while 7.7% of the isolates displayed colistin resistance associated with the mcr-3 gene. The bla_CTX-M-1 genotype was the most prevalent (57.7%), and almost half of the isolates harbored multiple ESBL genes. Phylogroup A (46.2%) predominated, followed by the high-risk extraintestinal lineages B2 (23.1%) and D (11.5%). PFGE revealed high genetic heterogeneity, with 51 distinct pulsotypes indicating multiple sources of contamination, such as untreated municipal, agricultural and industrial waste. Additionally, 55.8% of the isolates were capable of forming biofilms. These results highlight the critical role of the Shkumbini river as a reservoir for highly resistant pathogens and emphasize the urgent need for integrated environmental surveillance and improved wastewater management in Albania.

Abstract: Construction and demolition waste (CDW) is the largest single waste stream in the European Union by weight (~39% of all EU waste), yet the EU’s circular material use rate stood at only 12.2% in 2024 — less than half its 2030 target. Despite two decades of legislative ambition, the 70% recovery target under Directive 2008/98/EC has not been genuinely achieved: apparent compliance by most Member States conceals widespread downcycling and inconsistent reporting. This review identifies five persistent barrier domains — legal, technical, social, behavioural, and economic — with regulatory fragmentation and secondary material devaluation as the most structurally entrenched. A decisive paradigm shift is observed in recent research, from material characterisation towards systemic circularity, digital demolition frameworks, and governance. Emerging technologies — including AI-powered sorting, Building Information Modelling, Digital Twins, and Digital Product Passports — hold transformative potential, while Design for Deconstruction represents a critical upstream strategy the sector has yet to mainstream. The forthcoming EU Circular Economy Act will introduce legally binding obligations for Member States. The 2026 Strait of Hormuz energy crisis has reframed CDW from an environmental concern into a strategic industrial imperative: as virgin material costs surge, secondary CDW materials offer economic and geopolitical advantage. Future research must prioritise collaborative governance, longitudinal data, and scalable digital solutions.

Abstract: Accurate monitoring of soil salinization in arid oasis regions is crucial for agricultural sustainability and ecological security. However, existing deep learning-based approaches often suffer from insufficient utilization of multi-scale information and inadequate modelling of feature interactions, limiting their accuracy in retrieving complex salinity patterns. To address these limitations, this study proposes a scale-attention optimized hybrid deep learning model that integrates multi-scale 1D convolutional neural networks (1D-CNN), bidirectional gated recurrent units (Bi-GRU), and Transformer mechanisms. The model employs a multi-scale feature extraction module to capture remote sensing signals across different scales, a scale attention mechanism to adaptively weight the most informative features, and a Bi-GRU-Transformer module to explore complex sequential and global feature relationships. The proposed framework is applied to the oasis irrigation zone in Weili County, Xinjiang, using hyperspectral data from the ZY-1E satellite, topographic indices, and spectral-derived variables. Experimental results demonstrate that our method achieves a coefficient of determination (R²) of 0.952 and a root mean square error (RMSE) of 0.867 g·kg⁻¹ on the test set, outperforming conventional 1D-CNN, GRU-Transformer, and other benchmark models with improvements of 2.8% in R² and 18.9% in RMSE.

Abstract: Objectives: To descriptively evaluate the feasibility and clinical utility of TowardPi BO (4K ultra HD microscope integrated with a 400 kHz swept-source intraoperative optical coherence tomography (SS-iOCT) system) in managing various ophthalmic surgical conditions in a real-world setting. Methods: We analyzed surgical videos and data from 123 consecutive cases that underwent elective surgery with the assistance of this SS-iOCT system at Beijing Tongren Hospital between September 2, 2025, and February 10, 2026. Surgical cases were included based on specific diagnoses for which the SS-iOCT was found to be demonstrably useful. All videos were reviewed, and the utility of iOCT was discussed. Results: A total of 72 surgical cases were included, comprising 7 intraocular lens implantations with ciliary sulcus fixation, 19 macular holes, 3 cases of macular hole retinal detachment (MHRD), 4 cases of macular schisis with or without foveal detachment (MSRD), 12 cases of submacular hemorrhage, 20 cases of rhegmatogenous retinal detachment (RRD), and 7 intraocular mass lesions. The 400 kHz SS-iOCT significantly aided in surgical visualization, guided real-time decision-making, and prompted modifications in surgical techniques. Conclusions: This study presents the first report on 400 kHz SS-iOCT application in intraocular tumors. From routine surgical teaching to complex case management, SS-iOCT enhances surgical precision and facilitates real-time decision-making, ultimately contributing to improved surgical outcomes.

Abstract: The valorization of agro-industrial by-products through sustainable extraction of bio-compounds is a key challenge within circular economy and clean-processing frameworks, as large volumes of tomato and artichoke residues are generated by the food industry. This study evaluated the impact of non-thermal technologies on the recovery of biocompounds from tomato peels and blanched artichoke bracts using single green solvents instead of solvent mixtures. Ultrasound-assisted extraction (sonication), high-pressure processing (pressurization), and dual processing (pressurization + sonication) were compared with conventional extraction. Ethanol was used for lycopene extraction, while water was employed for inulin-type fructans recovery. Lycopene, total phenolic content, antioxidant activity, and inulin-type fructans were quantified. Non-thermal treatments significantly influenced extraction yields (p < 0.05). The dual processing provided the highest lycopene and inulin-type fructans contents (1440.09 ± 0.71 µg/g DW and 5.17 ± 0.51 g/100 g DW, respectively) and enhanced antioxidant activity in tomato peels and blanched artichoke bracts (25.50 ± 0.20% and 66.11 ± 2.03%), as well as phenolic co-extraction (1783.2 ± 215.3 μg GAE/g DW and 27.68 ± 1.29 mg GAE/g DW) outperforming individual technologies and conventional extraction. Compared with the conventional process, dual processing improved the extraction yields of lycopene (20.60 ± 0.44%) and inulin (26.40 ± 13.95%). The findings prove that non-thermal processes, particularly when combined, intensify mass transfer and enable efficient extraction using green solvents, offering a sustainable strategy for recovering bioactive compounds from tomato and artichoke by-products.

Abstract: Urban planners need continuous, scalable methods to evaluate pedestrian Level of Service (LOS). Static and locally calibrated approaches fail to capture the dynamic, network-wide, and context-dependent nature of pedestrian activity. While traditional LOS uses fixed density thresholds and data-driven models predict continuous flows, neither supports cross-city analysis due to context-specific assumptions. This study introduces a transferable analytical framework for predicting pedestrian LOS using large scale urban sensor data that captures both recurrent temporal demand patterns and spatial dependencies within street networks. The framework is evaluated using pedestrian sensor data from three cities Melbourne, Dublin, and Zurich, which represent diverse geometries, demand profiles, and sensing infrastructures. Results show strong in-domain Melbourne performance (accuracy 79.7%; Acc±1 99.1%) and effective cross-city generalization. Few-shot fine-tuning with only 5% labeled target-city data recovers 95–99% of in-domain performance, demonstrating practical scalability. KernelSHAP explainability reveals short-term temporal lag features universally dominate predictions, while spatial/contextual factors exhibit city-specific influence tied to local morphology. These findings demonstrate transferable GeoAI methods can support real-time pedestrian congestion monitoring and evidence-based public-space management, offering planners a scalable decision-support tool to enhance walkability, safety, and equitable access to high-quality public spaces in contemporary cities.

Abstract: Background: Hypoxic-ischaemic injury (HI) is a major contributor to neurological deficits following stroke. Understanding the mechanisms of neuronal death or survival in response to oxygen and nutrient deprivation is essential to fully comprehend the pathogenesis of diseases and disorders that are associated with HI. Aim: The aim of this study was to develop a robust in vitro model of ischaemic stroke, as well as serve as a new in vitro tool for initial screening of potential therapeutics and identification of diagnostic markers of brain hypoxic injury. Methods: This study details and validates a comprehensive protocol for modelling HI using differentiated SH-SY5Y neuroblastoma cells (Neuron-Like Cells, NLCs). First, we optimized the differentiation process and confirmed the maturity and purity of NLCs via standard molecular markers. The NLCs exhibited functional excitotoxicity, demonstrating a graded cell death response to N-methyl-D-aspartate (NMDA), validating their functional application. To simulate HI, we initially optimized the oxygen-glucose deprivation (OGD) treatment using graded concentrations of CoCl2 (0.125mM to 2mM) in glucose-free media. NLCs were then subjected to the refined OGD protocol (1mM CoCl2 in glucose-free media) for 3 hours, followed by various periods of reoxygenation (1h, 3h, 6h, 12h, 18h, and 24h). Result: RNA sequencing revealed a distinct temporal transcriptional response to HI. Injury-associated genes, including heat shock proteins and stress markers, were significantly upregulated at 3 hours of reoxygenation, peaked at 6 hours, and declined thereafter, remaining above baseline at 24 hours. Upstream regulator analysis identified IL-1β, TNF-α, and HIF-1α as key drivers during OGD, with additional regulators emerging during reoxygenation. TNF-α and β-oestradiol were consistently identified across time points, while TGF-β1 and NTRK1 became prominent during peak injury and later phases. Analysis of secreted factors showed increased release of inflammatory (TNF-α) and neurotrophic (β-NGF, BDNF, VEGF) mediators with reoxygenation, while maximal cell death occurred at 24 hours. Conclusion: This study identifies a transient, time-dependent transcriptional cascade following hypoxic–ischaemic injury, highlighting a critical window for early neuronal response. The model provides a reproducible platform for studying neuronal injury and recovery, and identifies known (TNF-α, IL-β, and HIF-1α), context-specific (NTRK1 and TGF-β) and novel (β-oestradiol) regulators of the injury response with potential relevance for therapeutic targeting.

Abstract: The rapid growth of electromobility is increasing pressure on the adequacy of charging infrastructure deployed along major transport corridors. This study presents a simulation-based framework for assessing the operational performance of electric vehicle charging infrastructure along the S19 Rzeszów–Barwinek section, a 90 km corridor forming part of the TEN-T and Via Carpathia networks. The methodology combines microscopic traffic simulation in PTV Vissim with probabilistic charging-demand modeling for passenger cars and heavy-duty vehicles, enabling the analysis of infrastructure utilization, queue formation, and unmet charging demand under realistic corridor conditions. Three electric vehicle penetration scenarios were examined: 10%, 25%, and 45% of the traffic stream. The results show that the charging system remains stable under the 10% scenario, begins to experience local overload and recurring congestion at 25%, and reaches structural insufficiency at 45%, where utilization exceeds 100% and unmet demand rises markedly. A key finding is that heavy-duty electric vehicles constitute the dominant operational bottleneck due to longer charging times, higher energy requirements, and the limited number of dedicated charging points. An additional expansion variant indicates that increasing the number of heavy-duty charging points can substantially improve system performance and restore a safer utilization range. The study demonstrates that minimum regulatory compliance should be treated as a baseline rather than a sufficient planning target and that dynamic, scenario-based simulation offers an effective decision-support tool for the adaptive development of corridor charging infrastructure.

Abstract: This paper examines the evolving role of central banks in supporting the transition to a low-carbon economy within the framework of sustainable development objectives. While central banks are not directly responsible for climate policy, climate-related physical and transition risks increasingly affect their core mandates, including price stability, financial stability, and the resilience of the banking system. The study highlights the growing relevance of integrating Sustainable Development Goals (SDGs) into central banks’ analytical frameworks as a means of linking macroeconomic and financial dynamics with environ-mental and social transformations. Drawing on key institutional sources, including Eurostat’s SDG monitoring reports, NGFS Phase IV climate scenarios, and ECB and ESRB analyses, the paper explores how climate risks can be quantified and incorporated into monetary policy and financial stability assessments. It emphasizes the role of standardized climate scenarios and stress testing in evaluating both transition and physical risks, as well as the uneven distribution of these risks across sectors and regions. Furthermore, the paper discusses the ECB’s “Climate and nature 2024–2025” plan as a concrete step toward operationalizing climate considerations in monetary policy, supervision, and portfolio management. By combining SDG indicators with climate scenarios and stress test results, the research identifies potential synergies and trade-offs between sustainability objectives and central bank mandates. The findings contribute to a conceptual and empirical framework for assessing how central banks can support the green transition while maintaining macroeconomic and financial stability.

Abstract: Candida albicans is an opportunistic fungal pathogen of clinical relevance, and plant-derived antifungal agents have attracted interest because of rising resistance to conventional drugs. This study evaluated the in vitro antifungal activity of Mespilodaphne quixos (Lam.) Rohwer essential oil (EO) against C. albicans, modelled its concentration-dependent response using a one-factor response surface methodology (RSM) design, and investigated the interactions of its constituents with selected fungal targets by molecular docking. Freshly collected leaves were subjected to steam distillation, and the EO was characterised by GC/MS. Antifungal activity was determined using the Kirby–Bauer disc diffusion method. A one-factor RSM design was applied to model inhibition halo diameter as a function of EO concentration. Besides, 22 identified compounds were docked against 14-α-demethylase, Δ(14)-sterol reductase, and exo-β-(1,3)-glucanase. The EO was mainly composed of (E)-cinnamaldehyde (47.2%), caryophyllene (10.8%), and α-humulene (5.37%). The EO reached an inhibitory capacity of 87.3% relative to ketoconazole. The quadratic model showed good predictive performance. Molecular docking revealed favourable affinities for several sesquiterpenes: α-copaene showed the best interaction profile against 14-α-demethylase and Δ(14)-sterol reductase, whereas α-guaiene and spathulenol performed best against exo-β-(1,3)-glucanase. These findings provide preliminary in vitro and in silico evidence supporting the antifungal activity of M. quixos EO.

Abstract: Historically, the study of oral fungal species was limited by the inability to cultivate most of them. However, advances in metagenomic techniques have enabled the direct identification of microbial genomes from human samples, markedly broadening our understanding of the oral mycobiome. This literature review aims to analyze the available scientific evidence on the composition and dynamics of the oral mycobiome, as well as its influence on the development of local pathological conditions. The oral mycobiome is highly diverse, with emphasis on genus Candida, followed by Malassezia, Aspergillus, Saccharomyces, Cladosporium, Trichosporon and Geotrichum. Candida albicans remains the most frequently identified species in both health and diseases state. However, individuals with oral candidiasis present a higher detection of Candida dubliniensis, Candida parapsilosis, Pichia kudriavzevii, Antrodiella micra and Cladosporium sphaerospermum. In dental caries, C. albicans and C. dubliniensis are associated with advanced lesions, whereas Malassezia and Rhodotorula may exert protective effects against cariogenic bacteria. In periodontitis, an increase in yeast-bacteria interactions is observed. Additionally, C. albicans has been implicated in oral carcinogenesis through multiple mechanisms. These findings highlight the need for a deeper understanding of the oral mycobiome to enable early detection of oral diseases and the development of therapeutic approaches.