Search Results (99)

The Chang 8 Member of the Jinghe Oilfield in the Ordos Basin is a low-porosity, ultra-low-permeability reservoir with many faults and fractures, complex structures, and strong heterogeneity. Conventional logging curves do not clearly distinguish among different structural units, making it difficult to identify the internal structures of fault-fracture reservoirs. Current methods mainly use logging curves and rock mechanical parameters. In these reservoirs, experiments are costly, numerical simulations take a long time, and identification is often inefficient. To improve identification accuracy and efficiency, this study developed a two-layer Stacking ensemble model for the Chang 8 Member. The dataset was derived from conventional well-log data from five wells in the Chang 8 Member and contained 816 labelled depth samples. Among them, 569 original samples from wells A1, A2, and A3 were used for model development, while 247 samples from wells JH55P10 and JH2301H were reserved for independent well-level validation. In the first layer, a support vector machine (SVM), XGBoost, and a random forest (RF) were used as the base learners. The hyperparameters of the base learners were optimized using grid search and K-fold cross-validation. In the second layer, multinomial logistic regression was used as the meta-learner to integrate the class-probability outputs of the base learners and generate the final predictions. Individual models showed limitations in distinguishing the three internal structural units of fault-fracture reservoirs. By integrating the complementary outputs of the base learners, the Stacking model achieved an overall accuracy of 0.89, exceeding the accuracies of the individual models on the internal hold-out test set. The results indicate that the proposed framework can improve the accuracy and class balance of multi-class identification on the present dataset and provide a practical approach for the detailed evaluation of internal structural units in low-porosity, low-permeability fault-fracture reservoirs. Full article

Vertical cross-layer propagation of hydraulic fractures is critical for the efficient stimulation of interbedded sandstone reservoirs in the Lianggaoshan Formation. To investigate the vertical fracture propagation mechanisms and controlling factors in this complex lithological setting, a three-dimensional (3D) numerical model was established using the continuum–discontinuum element method (CDEM) based on the typical “mudstone–sandstone–mudstone” geological structure of the Lianggaoshan Formation. The effects of geological parameters, including interlayer stress contrast, vertical stress contrast, elastic modulus ratio, and reservoir thickness, as well as engineering parameters, including fluid viscosity and injection rate, were systematically evaluated. The results show that interlayer stress contrast is the primary factor restricting vertical fracture growth. As the interlayer stress contrast increases from 2 MPa to 8 MPa, the fracture morphology gradually changes from effective cross-layer propagation to complete containment within the sandstone layer, while the injection pressure at 300 s increases from 55.91 MPa to 58.90 MPa and the fracture width increases from 4.58 mm to 5.05 mm. In contrast, vertical stress contrast has a limited influence under the horizontal-stratification conditions investigated. Increasing fluid viscosity and injection rate can enhance intra-fracture net pressure and promote interface breakthrough. When the fluid viscosity increases from 5 mPa·s to 50 mPa·s, the breakdown pressure increases from 61.05 MPa to 69.59 MPa and the fracture width increases from 4.79 mm to 6.37 mm. When the injection rate increases from 0.6 m³/min to 3.6 m³/min, the breakdown pressure increases from 58.57 MPa to 63.35 MPa and the fracture width increases from 4.28 mm to 5.17 mm. Based on the Effective Vertical Propagation Index (EVI), three vertical propagation modes were identified: restricted vertical propagation, partially effective cross-layer propagation, and effective vertical propagation. Gray Relational Analysis (GRA) revealed the following sensitivity ranking: interlayer stress contrast > injection rate > fluid viscosity > elastic modulus ratio > reservoir thickness > vertical stress contrast. For reservoirs with a typical 4 MPa stress barrier, effective vertical breakthrough can be achieved when the fluid viscosity exceeds 25 mPa·s or the injection rate reaches 3.6 m³/min. These findings provide quantitative guidance for optimizing fracturing parameters in interbedded sandstone reservoirs. Full article

Tight oil reservoir quality and development effectiveness are highly dependent on microscopic pore structure characteristics and spatial heterogeneity. In this study, tight sandstones from the Chang 3, Chang 6, Chang 7, and Chang 8 members of the Triassic Yanchang Formation in the Xunyi exploration area, southern Ordos Basin, were selected as research objects. By integrating X-ray diffraction (XRD), cast thin sections, scanning electron microscopy (SEM), high-pressure mercury injection (HPMI) experiments, and multifractal theory, the multi-scale heterogeneity characteristics of pore structures in different layers were quantitatively characterized. The response relationships between multifractal parameters, macroscopic physical properties, and pore size distributions were discussed, and the geological control mechanisms of sedimentation and diagenesis on heterogeneity were revealed. The results indicate that the sedimentary environment plays a fundamental role in controlling reservoir physical properties. The Chang 3 and Chang 8 members, deposited in underwater distributary channels, are dominated by primary and dissolution pores, with physical properties significantly superior to the gravity flow-deposited Chang 6 and Chang 7 members. Multifractal analysis shows that the Chang 3 member has the largest singularity spectrum width (Δα =1.943 ± 0.56) and heterogeneity index (R_d = 1.782 ± 0.99), reflecting its broadest pore size distribution, strongest heterogeneity, and significant intra-layer differences; while the pore structures from Chang 6 to Chang 8 are relatively stable, with the Chang 8 member exhibiting high spatial connectivity. This study demonstrates that the quantitative evaluation method based on multifractal theory can effectively identify microscopic structural differences in tight sandstones, providing a critical supporting basis for reservoir classification characterization and favorable layer selection in the Yanchang Formation of the Ordos Basin. Full article

Introduction: Freshwater fish communities in Mediterranean basins have undergone profound changes over recent decades due to biological invasions, habitat alteration, and hydrological regulation. The Segura River basin (SE Spain), particularly in the Region of Murcia, represents a paradigmatic case of these transformations, with increasing pressures on native ichthyofauna and growing relevance for recreational fisheries. Objective: This study aims to provide an updated inventory of fish communities in the rivers and reservoirs of the Region of Murcia, assessing current composition, relative abundance, and conservation status. Methodology: Fish assemblages were surveyed during sampling campaigns conducted in autumn 2023, 2024 and 2025. Sampling sites included representative reservoirs and river reaches within the middle sector of the Segura River basin, focusing on areas of interest for recreational fishing. Passive fishing gears were used in reservoirs, while electrofishing was conducted in riverine habitats. Presence and relative abundance data were recorded for all detected taxa. Results: A total of 15 taxa were identified (8 in reservoirs and 15 in river reaches). Reservoir communities were almost entirely dominated by non-native invasive species, including Cyprinus carpio, Alburnus alburnus, Sander lucioperca, Micropterus salmoides, Lepomis gibbosus, and Gambusia holbrooki, with Luciobarbus sclateri as the only native species. Riverine sections of the main channel also showed a strong dominance of exotic taxa, with additional species such as Esox lucius, Oncorhynchus mykiss, Gobio lozanoi, and Pseudochondrostoma polylepis. Native species detected included L. sclateri (dominant), Anguilla anguilla, and Salariopsis fluviatilis, the latter showing a recent expansion likely linked to human-mediated introduction. Isolated tributaries hosted the most valuable assemblages, including populations of L. sclateri, Squalius tartessicus, and the endangered Valencia hispanica (recently unauthorized translocations into the Segura river basin). Conclusions: Current fish communities in the Region of Murcia reflect a marked ecological degradation compared to historical conditions, driven by the proliferation of non-native species and habitat alteration. Changes over the last 30 years have been particularly pronounced in reservoirs and regulated sections of the main river channel, where local extinction of the native S. tartessicus has also been detected. Only the headwaters of certain tributaries retain fish assemblages of notable conservation interest, highlighting their priority for management and protection. Full article

Tight sandstone reservoirs exhibit strong pore-throat heterogeneity, which exerts important controls on reservoir quality and fluid-flow behavior. To investigate the pore-throat structure characteristics and their influence on permeability, integrated analyses of thin sections, X-ray diffraction (XRD), scanning electron microscopy (SEM), cathodoluminescence (CL) and mercury intrusion porosimetry (MIP) were conducted on the Chang 8 tight sandstones in the southern Ordos Basin (China). Results show that the Chang 8 tight sandstones are characterized by low porosity and ultra-low permeability, with average porosity and permeability of 7.5% and 0.331 mD, respectively. The pore systems mainly include intergranular, intragranular pores, intercrystalline micropores and microfractures, reflecting strong pore-throat heterogeneity. Segmented MIP analysis reveals two distinct pore-throat response intervals. The fine pore-throat segment shows valid fractal scaling, whereas the large pore-throat segment is interpreted as an early-stage intrusion response. A dimensionless MIP-derived heterogeneity index (H_MIP) was therefore used to characterize connected pore-throat heterogeneity. H_MIP ranges from 2.446 to 2.973 and shows negative associations with permeability and pore-throat radius, indicating that finer and more heterogeneous connected pore-throat systems are generally associated with lower flow efficiency. H_MIP exhibits weak to moderate associations with mineral composition, particularly with carbonate and quartz contents, whereas feldspar and clay minerals show limited relationships. Sensitivity analysis of characteristic pore-throat radii demonstrates that r₁₀ shows the strongest association with permeability within the present MIP dataset, and model performance decreases monotonically from r₁₀ to r₅₀, suggesting that early mercury-accessible coarse pore-throats are more closely related to effective fluid flow than smaller pore-throat populations in the Chang 8 tight sandstone reservoirs. These findings suggest that permeability in the Chang 8 tight sandstones is closely associated with the development of connected large pore-throats, whereas H_MIP provides empirical information on connected pore-throat heterogeneity and flow-path complexity. Full article

The Chang 8 tight oil reservoir in the Xifeng area of the Ordos Basin is characterized by poor reservoir properties, making conventional water flooding ineffective for efficient reservoir development. CO₂ flooding is therefore considered an important approach for enhancing oil recovery in tight reservoirs. However, suitable development strategies for direct CO₂ injection in undeveloped reservoir areas remain insufficiently understood. In this study, compositional numerical simulation combined with a single-factor sensitivity analysis was employed to investigate the effects of key parameters, including well pattern configuration, fracturing parameters, injection–production strategy, and gas injection modes. The results indicate that an inverted nine-spot well pattern with vertical well injection and vertical well production, a well spacing of 500 m, and a row spacing of 200 m can achieve relatively favorable areal and vertical sweep performance. A fracture half-length of 80 m, fracture widths of 0.003–0.005 m, and fracturing treatment before initial production help balance early-stage productivity and gas channeling control. Maintaining an injection rate of 0.03–0.04 PV/a, an oil production rate of 2–3 m³/d, and a bottomhole flowing pressure of 13–14 MPa is beneficial for maintaining reservoir energy and stabilizing displacement-front propagation. Based on neighboring field development experience, switching from continuous CO₂ injection to water–alternating–gas (WAG) injection during the mid-development stage can improve mobility control and enlarge the CO₂ swept volume. Under the current geological model and simulation conditions, the recommended development strategy predicts a recovery factor of 35.43% over a 30-year production period. The results provide reasonable parameter ranges and an engineering reference for direct CO₂ flooding development in the Chang 8 tight oil reservoir and similar reservoirs. Full article

The pore-throat structure is a key factor in the exploration and development of tight sandstone reservoirs. In the present study, 14 tight sandstone samples from the Chang 8 member of the Ordos Basin were analyzed using high-pressure mercury intrusion, cast thin section analysis, scanning electron microscopy and cathodoluminescence imaging techniques. Fractal dimensions, obtained from the slopes of log(S_W) versus log(P_c) double-logarithmic plots, were applied to quantitatively characterize pore-throat structures and classify reservoirs through multifractal analysis, and discuss the diagenetic controlling factors affecting the pore-throat structure of different reservoir types. The results showed that the Chang 14 tight sandstones are characterized as two segments fractal features, which indicated that these samples have complex pore-throat structure and consist of two types of spaces: mesopore-throat spaces and micropore-throat spaces. The mesopore-throat system shows a higher fractal dimension (D1: 2.74–2.99), indicating greater heterogeneity and irregularity, while the micropore-throat system exhibits a lower dimension (D2: 2.28–2.61). D1 exhibits a negative correlation with the porosity and permeability of mesopores, while D2 shows a weak positive correlation with the properties of micropores. The total fractal dimension (D) is weakly correlated with overall reservoir properties, confirming that reservoir storage and flow capacity are primarily governed by the mesopore system rather than the micropore system. By analyzing the contribution of pore throats to sample physical properties, the results indicate that the 14 samples can be classified into two types based on 35% porosity contribution and 60% permeability contribution thresholds. Type 1, reservoirs dominated by microporous throat space (D values ranging from 2.603 to 2.644); Type 2, reservoirs dominated by mesoporous throat space (D values ranging from 2.544 to 2.598). Type 1 is characterized by primary intergranular pores, residual intergranular pores and intergranular dissolution pores, which enhance connectivity and reduce network complexity, thereby improving fluid permeability. In contrast, Type 2 consists mainly of intragranular dissolution pores, intergranular gap pores and micro-dissolution pores in clay minerals, which significantly inhibit fluid mobility. Diagenesis, including compaction, dissolution and cementation, exerts a significant control on the fractal characteristics and pore-throat structure evolution. The fractal characteristics exhibited in the pore-throat structure could provide a desirable analytical method, distinguishing from classification based on scale or size, for the evaluation and classification of tight sandstone reservoirs. Full article

There are several methods which are utilized for flooding oil process monitoring, such as the seismic methods, and the electromagnetic methods. As the gas flooding oil process is complicated, conventional methods are not capable of monitoring the gas flooding oil process accurately. This study utilizes the Ground Penetrating Radar (GPR) method to monitor the CO₂ flooding oil and water flooding oil processes, as the difference in dielectric constants and conductivity of CO₂, oil and water is utilized to infer distributions of CO₂, oil and water. Moreover, as GPR data processing is time-consuming, it is impossible to process the GPR data in real-time by a conventional method, such as the full waveform inversion method. This study utilizes U-Net neural networks to invert for the subsurface dielectric constants and conductivity distributions of CO₂, oil and water in real-time. A deep learning inversion network based on the U-Net architecture is trained to extract multi-scale features through an encoder–decoder structure, achieving an end-to-end mapping from GPR echo signals to subsurface electrical parameters. The study utilizes the gprMax forward tool to simulate the dynamic response changes in rock-electrical parameters during flooding and constructs a high-resolution training dataset of 100,000 samples. Each sample contains the relationships between a subsurface electrical parameter model and its corresponding multi-transmitter, multi-receiver GPR responses. This method was first tested by the synthetic data of oil–water flooding and oil–water–gas flooding, and then it was tested by observed data from physical core experiments. Numerical and physical core experimental results show that the method accurately inverts the electrical parameter distributions of oil, water, and gas in the sandstone model, successfully capturing the position and morphology changes in the displacement front. The average relative error of dielectric constant inversion is controlled within 8% with the error mainly from the low dielectric constant regions and the relative error of conductivity is smaller than 10%, with the error mainly concentrated in high-conductivity water regions for conductivity inversion results. The results reveal the feasibility and superiority of the neural network-based deep learning method in GPR electromagnetic inversion, providing a new method for real-time flooding monitoring and intelligent reservoir development during oil and gas flooding. Moreover, the proposed approach offers a fast inversion solution and is less affected by the initial model and noise. Full article

Dam constructions alter the river flow, leading to a cascade of physical, chemical, and biological changes in the ecosystem’s structure and function. This study presents a systematic framework for assessing the impact of these built structures on adjacent surface water bodies. The approach integrates mandatory long-term monitoring data with a multivariate statistical approach (Partial Least Squares Discriminant Analysis, PLS-DA) to provide a robust assessment of fourteen of Bulgaria’s major and significant reservoirs’ influence on nearby rivers and streams. Datasets for studied reservoirs include basic physicochemical parameters, and for 8 out of 14 dams—potentially toxic elements (PTEs). To assess the influence of each reservoir on the river, two sampling locations were selected per dam: upstream (U) and downstream (D). Results for the water quality parameters, identified as significant discriminators in each PLS-DA model, are presented. A clear upstream dominance was observed for Pchelina, Saedinenie, and Ticha, a strong downstream pattern was observed for Dospat and Yovkovtsi, and a mixed spatial pattern for the remaining dams. The hierarchical clustering revealed three groups of parameters studied. The first cluster (EC, NO₂⁻, NO₃⁻, TN) likely reflects diffuse inputs. The second cluster (TP, PO₄³⁻) describes the relationship between total and dissolved phosphorus fractions. The third cluster (pH, NH₄⁺, DO, BOD) highlights organic matter decomposition and oxygen dynamics. The results highlight that reservoir impacts are governed by the interplay of hydrological conditions, catchment characteristics, and in-reservoir biogeochemical processes, leading to distinct functional behaviours such as retention, transformation, or release of substances. Full article

High Andean lagoons in southern Peru have critical hydrological and ecological functions; however, long-term time series integrating trophic, integral quality, and metal contamination metrics to support adaptive management are lacking. A total of 1846 records (2015–2024) from four systems (3100–4600 m a.s.l.) were analyzed using seven indices assessing trophic status (TSItsr, TRIX), general water quality (OWQI, WQIHA, CCME-WQI), and metal contamination (HPI, CD). Temporal trends were assessed using Mann–Kendall and Theil–Sen slope; spatial heterogeneity using Kruskal–Wallis and Dunn–Bonferroni comparisons; controlling factors using distance-based redundancy analysis (999 permutations); and functional typology using Ward’s hierarchical clustering on Z-standardized data. 93% of the series lacked monotonic trends (52/56 lagoon–stratum × index combinations), demonstrating high interannual stability; spatial variance was marked (ε² = 0.73 in CCME-WQI). Distance-based redundancy analysis (db-RDA) explained 24.6% of total variability, with lake identity as the dominant driver (~45%), followed by temporal change (~8%). Four functional archetypes emerged, including a metal-eutrophic hotspot (HPI ≈ 213; CD ≈ 19) and recovering reservoirs with intermediate water quality indicators. Joint thresholds (TSItsr ≥ 60 + HPI ≥ 100) establish early-warning criteria, with Paucarani (HPI = 213) approaching the critical domain where metal-driven stress may facilitate cyanobacterial dominance. Systems show temporal resilience but strong spatial divergence induced by local pressures. The proposed typology and thresholds provide an operational basis for early warnings and prioritization of remediation actions in high-mountain ecosystems subject to increasing anthropogenic stress. Full article

Deep coalbed methane resource evaluation is limited by weak coupling among key controlling factors and by the lack of unified methods for Computational Unit delineation. This study focuses on the No. 8 coal seam of the Benxi Formation in the Ordos Basin. A geological–engineering integrated framework for delineation and evaluation of deep coalbed methane units was established based on the concept of “one body and four levels.” Results indicate that a depth of 1500 m represents a critical boundary for changes in coalbed methane occurrence. Gas in deep coal seams occurs mainly as a combination of adsorbed gas saturation and free gas enrichment. Vitrinite reflectance was used to evaluate gas source conditions, and a threshold of Ro = 1.2% was identified. Cap rock sealing performance was evaluated using lithological assemblages, with mudstone–limestone combinations showing the most favorable preservation conditions. A brittle–ductile index based on rock mechanical parameters was applied to assess reservoir fracability. Gas source effectiveness, preservation conditions, and reservoir transformability were quantified using thermal simulation experiments, formation pressure and temperature analysis, sealing tests, and coal–rock mechanical experiments. GIS-based spatial overlay analysis was used to divide the No. 8 coal seam into 16 computational units. The total deep coalbed methane resources were estimated at approximately 16.49 × 10¹² m³. Accordingly, the research findings provide a crucial scientific basis for the rational delineation of computational units in deep coalbed methane systems. They also offer significant theoretical support for subsequent applications of machine learning and coupled geomechanics–flow modeling methods, enabling accurate dynamic prediction and optimal zone selection within the study area. Full article

The Chang 8 Member in the Longdong area of the Ordos Basin hosts significant petroleum resources, demonstrating substantial potential for tight oil exploration and development. Astronomical forcing exerts a discernible influence on the evolution of its petroleum system. To elucidate the impact of Milankovitch orbital cycles on organic enrichment and the development of source rocks, reservoirs and cap rocks, we conducted a high-resolution cyclostratigraphic analysis of the Chang 8 Member stratigraphy. This study utilized gamma-ray (GR) well log series as the primary dataset. This lacustrine succession preserves distinct Milankovitch cycles, including ~405 ka long eccentricity, ~125 ka short eccentricity, obliquity, and precession periods, with eccentricity cycles showing particularly strong expression. These diagnostic eccentricity signals provided the framework for delineating high-frequency sequences. Subsequent astronomical tuning and base-level reconstruction constrain the depositional age of the Chang 8 Member to 242.22–241.23 ± 1.4 Ma. During this interval, the lacustrine system exhibited a pronounced trend of base-level fall followed by rise, punctuated by higher-frequency fluctuations. Milankovitch cycles govern the development of high-quality reservoirs and cap rocks and organic enrichment by modulating climate and lake-level fluctuations. These orbital forcings drive weathering processes, control fluvial sediment supply and lacustrine accommodation space, and influence biological productivity. Our results demonstrate a pronounced association between the long eccentricity cycle (~405 ka) and enhanced reservoir quality development, while the short eccentricity cycle (~125 ka) exhibits a stronger correlation with organic matter enrichment, cap rocks, and source rock formation. Ultimately, the interplay of eccentricity cycles jointly governs the formation of the hydrocarbon system within the continental Chang 8 Member. Full article

Accurate reservoir identification from well-logging data is crucial for hydrocarbon exploration, yet challenges persist due to a series of factors, including limitations such as low efficiency and subjectivity of manual processing for massive datasets, as well as class imbalance and its impact on machine learning model training. This study develops an intelligent identification model using a Convolutional Neural Network (CNN) enhanced with Focal Loss, applied to real well-logging data from the Chang 8 Member of the Yanchang Formation in the Jiyuan Oilfield, Ordos Basin. A well-based data partitioning strategy is adopted to ensure the model’s generalization ability to new wells, avoiding the overoptimistic performance associated with random sample splitting. Experimental results demonstrate that the proposed model achieves an Accuracy of 84% and a Recall of 83% for oil-bearing layers. In comparison, the Random Forest model achieves a lower Recall of 56% for oil-bearing layers, and the CNN-LSTM model achieves 77%. The key influential well-logging parameters identified are bulk density (DEN), spontaneous potential (SP), true resistivity (RT), and natural gamma ray (GR). The findings confirm that the Focal Loss-enhanced CNN effectively mitigates class imbalance issues and provides a reliable, automated method for reservoir identification, offering significant practical value for the secondary interpretation of well logs in similar tight sandstone reservoirs. Full article

Globally, lakes are increasingly recognized as sensitive indicators of climate change and ecosystem stress. Qaraoun Lake, Lebanon’s largest artificial reservoir, is a critical resource for irrigation, hydropower generation, and domestic water supply. Over the past 25 years, satellite remote sensing has enabled consistent monitoring of its hydrological and environmental dynamics. This study leverages the advanced cloud-based processing capabilities of Google Earth Engine (GEE) to analyze over 180 cloud-free scenes from Landsat 7 (Enhanced Thematic Mapper Plus) (ETM+) from 2000 to present, Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) from 2013 to present, and Landsat 9 OLI-2/TIRS-2 from 2021 to present, quantifying changes in lake surface area, water volume, and pollution levels. Water extent was delineated using the Modified Normalized Difference Water Index (MNDWI), enhanced through pansharpening to improve spatial resolution from 30 m to 15 m. Water quality was evaluated using a composite pollution index that integrates three spectral indicators—the Normalized Difference Chlorophyll Index (NDCI), the Floating Algae Index (FAI), and a normalized Shortwave Infrared (SWIR) band—which serves as a proxy for turbidity and organic matter. This index was further standardized against a conservative Normalized Difference Vegetation Index (NDVI) threshold to reduce vegetation interference. The resulting index ranges from near-zero (minimal pollution) to values exceeding 1.0 (severe pollution), with higher values indicating elevated chlorophyll concentrations, surface reflectance anomalies, and suspended particulate matter. Results indicate a significant decline in mean annual water volume, from a peak of 174.07 million m³ in 2003 to a low of 106.62 million m³ in 2025 (until mid-November). Concurrently, pollution levels increased markedly, with the average index rising from 0.0028 in 2000 to a peak of 0.2465 in 2024. Episodic spikes exceeding 1.0 were detected in 2005, 2016, and 2024, corresponding to documented contamination events. These findings were validated against multiple institutional and international reports, confirming the reliability and efficiency of the GEE-based methodology. Time-series visualizations generated through GEE underscore a dual deterioration, both hydrological and qualitative, highlighting the lake’s growing vulnerability to anthropogenic pressures and climate variability. The study emphasizes the urgent need for integrated watershed management, pollution control measures, and long-term environmental monitoring to safeguard Lebanon’s water security and ecological resilience. Full article

Aging of the gut involves progressive changes in structure, function, and microbial composition, which impact overall health. The vermiform appendix extends from the apex of the cecum; it contains gut-associated lymphoid tissue and serves as a reservoir of gut microbiota. This study investigates histologic and gene expression changes in 20 morphologically normal appendiceal samples obtained from pediatric (n = 5), adult (n = 8), and geriatric (n = 7) patients. Histologic analysis revealed a higher prevalence of lymphoid follicles reduction and the presence of fibrous obliteration of the appendiceal tip in aged samples. RNA sequencing identified 1004 differentially expressed genes (385 upregulated and 619 downregulated; p < 0.05) between the adult and geriatric population. Upregulated pathways were enriched for oxidative stress response, cholesterol metabolism, and mucosal barrier maintenance, including NRF2 targets (NQO1, MGST1), suggesting enhanced antioxidant activity. Downregulated genes were associated with synaptic signaling, ion channel regulation, and neuronal adhesion (e.g., GRIA2, RET, NOS1, NCAM2, CNTN1), reflecting age-related decline in enteric neuronal integrity. Across all age groups, 25 protein-coding genes showed progressive expression shifts with aging, including upregulation of CLDN2, MUC2, and GDF15, and downregulation of NOG and NELL2, indicating barrier loosening, chronic inflammation, and reduced regenerative potential. These findings suggest that aging of the vermiform appendix recapitulates key processes of intestinal aging, including oxidative stress, inflammaging, and neuronal loss, supporting its potential use as a model tissue for studying gut aging mechanisms. Full article