Search Results (563)

Fungal infections remain a major threat to human health, with non-albicans Candida (NAC) species causing more than half of all clinical cases and many strains gaining resistance to current treatments rapidly. Previously, N-arachidonoyl ethanolamine (anandamide, AEA) has been studied and shown to possess antibacterial and antifungal properties against various bacteria and Candida albicans. Given the previous findings, we aim here to expand the current preliminary research on AEA to investigate its antifungal activities against clinically relevant NAC species in vitro: Candida glabrata, Candida parapsilosis, and Candidaozyma auris. The minimum inhibitory concentration (MIC) and growth curve analysis determined planktonic inhibition. MTT metabolic assay and ATP production via BacTiter-Glo luminescence assay evaluated biofilm formation. Membrane fluidity, polarization and efflux pump activity were examined using fluorescence probes Laurdan, DiS-C3(3), and Rhodamine 6G, respectively. Reactive oxygen species (ROS) were assessed using DCFH-DA. Biofilm architecture and cell viability were analyzed by spinning disk confocal microscopy (SDCM). AEA reduced MIC values and slowed planktonic growth, while MTT and ATP assays demonstrated a pronounced dose-dependent reduction in biofilm metabolic activity. Membrane-targeted effects revealed increased fluidity and permeability at 125 µg/mL. Notably, AEA rapidly impaired efflux pump activity and induced intracellular ROS production. This effect was accompanied by reduced cell viability, increased proportions of PI-positive cells, and enhanced intracellular dye retention, as confirmed by SDCM. Together, these findings demonstrate that AEA exerts antifungal activity by disrupting membrane integrity and associated cellular functions and provide the first comparative characterization of species-specific membrane and oxidative stress responses to AEA across three major clinically relevant multidrug-resistant NAC species. Full article

Constructed wetlands (CWs) are widely used as an ecological technology for wastewater treatment. However, the accumulation of microplastics (MPs) in their substrates may impair long-term performance and threaten the operational sustainability of these nature-based treatment systems. To elucidate the transport behaviour of MPs in wetland substrates, this study developed a numerical model based on the lattice Boltzmann method (LBM) to simulate advection, hydrodynamic dispersion, and reversible first-order adsorption/desorption of MPs in saturated porous media. The model incorporates a salinity-dependent non-linear attachment rate coefficient, which captures the compression of the electrical double layer and the enhanced attachment efficiency with increasing salinity. Pore-scale flow is solved using the LBM with an Ergun-type drag term to represent the resistance of the porous matrix. The model was validated against experimental breakthrough curves from column studies using quartz sand and coastal wetland soils under five salinity levels (0–35 PSU) reported in the literature. Quantitative validation yielded coefficients of determination (R²) ranging from 0.782 to 0.960 (RMSE = 0.024–0.045) for calibration cases and 0.741 to 0.946 (RMSE = 0.027–0.048) for independent validation cases across both substrates, excluding the soil cases at 3.5 and 35 PSU. Here, both observed and simulated effluent concentrations were identically zero, resulting in the statistically forced R² = 1.000 and RMSE = 0, which are mathematical artefacts rather than indicators of predictive performance. The simulations reproduce the observed reduction in peak relative concentration by over 50% in sand and near-complete retention (C/C₀ ≈ 0) in soil at high salinities (3.5 and 35 PSU). Results demonstrate that the model successfully reproduces the differences in MP breakthrough behaviour across different substrate types and salinity levels. By linking salinity-enhanced retention to the risk of irreversible clogging and shortened wetland lifespan, the model provides a predictive tool for evaluating the sustainability of CWs under saline stress. This study offers a scientific basis for optimizing hydraulic management (e.g., flushing strategies) to mitigate microplastic pollution and enhance the long-term sustainability and resilience of constructed wetlands in coastal and saline environments. Full article

The complexity of micrometer-scale pore-throat structures in sandstone reservoirs strongly controls the occurrence state and mobilization degree of residual oil after water-flooding. To clarify the differences in residual oil occurrence between pure oil-zone and transition-zone reservoirs and their microscopic controlling mechanisms, sandstone samples were collected from the SII oil layer group, which belongs to the Upper Cretaceous Yaojia Formation, in the Nanqi area of the Daqing Oilfield, northern Songliao Basin, NE China, and were investigated. Mercury intrusion capillary pressure (MICP), two-dimensional nuclear magnetic resonance (2D NMR), laser scanning confocal microscopy (LSCM), micro-computed tomography (micro-CT), X-ray diffraction (XRD), wettability measurement and fractal analysis were integrated to systematically characterize the pore-throat architecture, mineral composition, seepage capacity, and residual oil occurrence of the two reservoir types. The results show that the pore-throat radius distributions are mainly unimodal. In the pure oil-zone samples, the pore-throat distribution is highly consistent with the corresponding permeability contribution curve, whereas evident deviations occur in some transition-zone samples. Large and medium pore throats exert the most significant control on seepage capacity, and the difference in fractal characteristics is mainly reflected by D1, the fractal dimension of large pore throats. The transition-zone reservoirs generally exhibit moderate to strong water-wet characteristics. Owing to the development of fine pore throats and strong capillary forces, water is prone to retention within pore-throat spaces, resulting in pronounced water-blocking and Jamin effects. After water-flooding, the pure oil-zone reservoirs exhibit lower residual oil saturation, with residual oil occurring mainly in a bound state; in contrast, the transition-zone reservoirs show higher residual oil saturation and relatively high proportions of free and semi-bound residual oil. Mineral composition further modifies pore-throat complexity and residual oil occurrence. D1 is negatively correlated with feldspar content, indicating that increased feldspar content helps improve the pore-throat structure, but positively correlated with clay mineral content, suggesting that clay minerals enhance structural complexity. In the transition-zone reservoirs, kaolinite and illite–smectite mixed-layer minerals are relatively well developed. Their velocity-sensitive and water-sensitive effects readily induce pore-throat blockage and increased flow resistance, which are important causes of residual oil enrichment and difficult oil mobilization in the transition zone. Full article

Hyptis eriocephala is an aromatic Lamiaceae species from southern Ecuador whose essential oil has not previously been characterized. To establish an initial phytochemical and biological baseline, aerial parts collected at Villonaco were subjected to three independent steam-distillation runs, yielding 0.13 ± 0.04% (w/w) essential oil. Volatile constituents were tentatively assigned by GC–MS using concordant EI mass-spectral and linear retention-index evidence, whereas relative composition was determined by GC–FID peak-area normalization without an internal standard, calibration curves, or response correction factors. Sixty-five constituents accounted for 96.81% of the total GC–FID peak area. The relative profile was dominated by hydrocarbon sesquiterpenes (67.88%), followed by hydrocarbon monoterpenes (24.36%), with α-copaene (28.20 ± 0.24%), germacrene D (9.29 ± 0.09%), α-pinene (6.98 ± 0.03%), α-cubebene (6.70 ± 0.06%), δ-cadinene (6.03 ± 0.07%), limonene (5.44 ± 0.05%), (E)-caryophyllene (5.31 ± 0.05%), and β-phellandrene (4.96 ± 0.02%) were the principal constituents. The oil showed a narrow antibacterial response, with MIC values of 250 µg/mL against Enterococcus faecium ATCC 27270 and 2000 µg/mL against Enterococcus faecalis ATCC 19433. Radical-scavenging activity was assay-dependent: activity was measurable in the ABTS assay (SC₅₀ = 76.87 ± 1.05 µg/mL; TEAC = 30.06 ± 1.16 µM TE/g EO), whereas 50% DPPH scavenging was not reached at 8000 µg/mL. The oil preferentially inhibited BuChE (IC₅₀ = 125.3 ± 1.03 µg/mL) over AChE (IC₅₀ = 385.9 ± 1.02 µg/mL). These findings establish a preliminary phytochemical and biological baseline for the Villonaco material but do not demonstrate a species-wide chemotype, mechanism of action, or therapeutic potential. Full article

The surface soil in the Shendong mining area is dominated by aeolian sand and sandy sediment, while precipitation is limited, and evaporation is intense. Under these conditions, shallow reconstructed soil has difficulty retaining plant-available water, which constrains vegetation restoration. This study evaluated how low-range increases in fine-particle clay content affect both water retention and upward water conduction in sandy reconstructed soil. Sandy material from the Shangwan mining area and exogenous river clay were mixed into four treatments, and soil water characteristic curves (SWCCs) were determined by centrifuge over 10–1000 kPa matric suction. The data were fitted with the Van Genuchten model and combined with capillary-rise tests. The results showed that increasing fine-particle content shifted the SWCC upward and raised both saturated and residual volumetric water contents. SN10 reached 17.18% and 5.55% volumetric water content at 10 and 1000 kPa, respectively, and its effective water capacity in the 33–1500 kPa range was 17.9% higher than that of ST. At the same time, fine-particle enrichment in the bottom layer reduced wetting-front rise during capillary testing, indicating a trade-off between water storage and upward replenishment. Within the tested fine-particle range, moderate clay addition improved the hydraulic performance of sandy reconstructed soil, but soil design should balance precipitation retention, infiltration, and capillary supply. Because each treatment and soil-column configuration was represented by only one independently prepared experimental unit, experimental variability and reproducibility could not be evaluated. This study should therefore be regarded as a preliminary and exploratory laboratory assessment conducted under a specific set of material-preparation procedures, specimen geometries, and boundary conditions. The results describe specimen-level hydraulic contrasts rather than reproducible treatment effects and should not be directly generalized to field-scale soil reconstruction. They support a preliminary hypothesis for future replicated testing: fine-particle enrichment may increase water retention while slowing upward capillary replenishment. Full article

This paper reports a research work on assessing clay content effect on the water retention capacity of clayey sandy soils. At first, experimental tests were conducted to measure the soil water retention curves (SWRCs) of clayey sandy soils. A total of four different soil samples, which have clay content of 0, 15, 30 and 50%, respectively, by total soil sample weight, were measured. Secondly, a revision of a physical–chemical (PC) analytical model previously proposed has been reviewed and adopted to represent the SWRC measurements and compared for its predictive performance against the classic van Genuchten model and the original PC model. The experimental results demonstrated that clay content has a significant influence on soil water retention capacity, showing that a positive correlation generally exists between them. The modelling results showed that the revised analytical model not only produced a good representation for the soil water retention curves over whole range of soil water content, particularly at low water content side, but also provided advanced insight into the fundamental physics underlying soil water retention mechanisms. The analysis of its parametric data highlights the functions of the involved physics and their roles shaping the SWRCs, which intrinsically relate to specific surface area, pore size distribution, and particle size and shape. At last, the model was used to describe the pore size distribution from a revised concept against conventional approach. However, the revised concept and approach needs further wide verification and is open for discussion. Full article

Event cameras provide high temporal resolution and sparse asynchronous output for small-target monitoring. However, distant weak targets often generate sparse and fragmented events that are easily obscured by responses from background structures and sensor background activity (BA) noise. This paper proposes a Spatio-Temporal Polarity Interaction Filter (SPIF), which assigns a reliability score to each incoming event. SPIF constructs weighted neighborhood support from temporal proximity, spatial distance, and polarity relationships, and uses the recent firing history of the center pixel to discount unreliable evidence caused by persistent activation. On the complete test split of the event-based unmanned aerial vehicle (EV-UAV) benchmark, SPIF achieves a macro-averaged F1 score (macro-F1) of 0.7732 and a target retention rate of 0.8896, exceeding the corresponding values of 0.7583 and 0.6740 obtained by the supervised EV-SpSegNet. Driving and the ED24 real-world denoising dataset further evaluate separation between valid events and BA noise. SPIF obtains the highest area under the receiver operating characteristic curve (AUC) on Driving at 3–10 Hz/pixel and under all evaluated ED24 settings. The C++ implementation processes 6.72 million events per second on the tested CPU. Full article

Severe fracturing-fluid retention and low post-fracturing flowback efficiency are common in the Lianggaoshan shale reservoirs of the Sichuan Basin. Liquid loading may also occur during late production. To address these problems, this study investigates a synergistic flowback technology that combines natural fracturing-fluid flowback with CO₂ gas lift. First, based on the complex fracture network characteristics of the Lianggaoshan shale reservoir, the interaction mechanisms between hydraulic fractures and natural fractures were investigated. An energy model for fracturing-fluid flowback under natural flowback conditions was established, revealing that reservoir gas expansion energy, hydromechanical energy, and rock elastic energy are the primary driving forces for fracturing-fluid flowback. Furthermore, considering fracture closure behavior, fluid leakoff, and wellbore flow dynamics, a calculation model for the natural flowback of fracturing fluid was developed, and a staged pressure-controlled flowback strategy was proposed. Subsequently, to address the decline in liquid unloading capacity caused by formation-energy depletion during the late stage of natural flowback, a gas-lift-assisted flowback multiphase flow model for the wellbore was established. The effects of the gas injection pressure, gas injection rate, and wellhead pressure on liquid unloading efficiency were systematically investigated. The results indicate that the liquid unloading rate increases with an increasing gas injection pressure and gas injection rate; however, a pronounced diminishing marginal effect is observed. For the Well H1 reference case, the central recommended gas injection pressure was 12 MPa, the gas injection rate was 8 × 10⁴–10 × 10⁴ m³/d, and the wellhead backpressure was maintained below 0.5 MPa. Furthermore, the CO₂-assisted flowback mechanisms were evaluated by distinguishing between the effects explicitly represented in the model and the potential reservoir-scale physicochemical effects. The reduction in wellbore mixture density and bottomhole flowing pressure was simulated directly, whereas CO₂–oil mass transfer, viscosity reduction, mineral dissolution, and changes in water-blocking behavior were interpreted with reference to published experimental studies. Based on these mechanisms, a three-stage synergistic optimized flowback scheme, consisting of “CO₂ soaking–natural flowback–CO₂ gas lift,” was established. A sequence of stagewise quasi-steady PIPESIM calculations was subsequently performed over the 30-day operating schedule. Under the adopted simulation conditions, the recommended soaking period is 5–7 days. The operation should be switched to gas lift when the wellhead pressure falls below 1.5 MPa or when daily liquid production declines continuously by more than 20%. Under the synergistic scheme, the 30-day cumulative flowback volume was predicted to reach 3492 m³. This value was substantially higher than those obtained by conventional natural flowback and standalone gas-lift processes. Moreover, the flowback curve exhibits a distinct “secondary surge” characteristic. These findings provide a theoretical basis and technical support for efficient fracturing-fluid flowback and stable long-term production in the Lianggaoshan Formation. They may also be applicable to other shale oil reservoirs with low porosity and ultra-low permeability. Full article

Biochar is a porous, carbon-rich soil amendment that can enhance soil water retention capacity by modifying pore structure and physicochemical properties. Understanding the soil−water characteristic curve (SWCC) of biochar-amended soils is essential for evaluating their hydrological behavior and promoting the application of biochar in engineering practice. Given the demonstrated feasibility and accuracy of machine learning methods for predicting soil parameters, this study employed six machine learning models, namely, decision tree, random forest, XGBoost, LightGBM, CatBoost, and artificial neural network, to predict the SWCC of biochar-amended soils based on a constructed dataset. Feature importance analysis and partial dependence analysis were further conducted to reveal the influence patterns of key variables. The results indicate that all six models exhibit good predictive capability, with gradient boosting models (XGBoost, CatBoost, and LightGBM) performing best. Suction is the dominant factor controlling the volumetric water content variation, while soil particle-size distribution and dry density provide the physical basis for water retention. Biochar content, pyrolysis temperature, and feedstock type further modulate the water retention capacity of amended soils. Overall, the findings demonstrate that machine learning approaches can effectively predict the SWCC of biochar-amended soils and provide insights into the controlling mechanisms of soil water retention. Full article

Aim: To establish and validate a quantitative transporter-mediated imaging framework based on gadoxetic acid-enhanced T1 mapping for assessing liver functional reserve (LFR) and to investigate the physiological significance of the relative change in longitudinal relaxation rate (ΔR1%) as a quantitative imaging biomarker. Methods: Female C57BL/6J mice (6–8 weeks old) representing five experimental liver conditions (control, transporter-deficient Slco1b2/Slco1a5 double-knockout, carbon tetrachloride-induced fibrosis, methionine–choline-deficient diet-induced steatohepatitis, and alcohol-associated fatty liver disease; n = 6 per group) underwent serial Gd-EOB-DTPA-enhanced T1 mapping. Quantitative ΔR1% was calculated to characterize hepatobiliary enhancement kinetics. Liver functional reserve was independently evaluated using multispectral optoacoustic tomography of indocyanine green (ICG) pharmacokinetics and serum ICG retention assays, with histopathological and hepatocellular transporter analyses performed for mechanistic validation. Longitudinal data were analyzed using restricted maximum likelihood (REML)-based mixed-effects models. Intergroup comparisons were performed using one-way ANOVA or Kruskal–Wallis tests with appropriate post hoc analyses, and associations between imaging and functional parameters were evaluated using Spearman rank correlation analysis. A two-sided p < 0.05 was considered statistically significant. Results: Five experimental liver models exhibited distinct transporter-dependent hepatobiliary enhancement patterns. The transporter-deficient knockout mice showed minimal enhancement, whereas fibrosis and steatotic liver injury models demonstrated intermediate but clearly distinguishable functional profiles. Longitudinal mixed-effects analysis identified significant effects of time, experimental group, and time-by-group interaction on ΔR1% dynamics (all p < 0.0001). Although MRI-derived ΔR1% parameters were not significantly correlated with regional optoacoustic ICG kinetics, ΔR1% area under the curve showed a strong inverse correlation with serum ICG retention at 600 s (r = −0.729, p < 0.0001), indicating that MRI-derived ΔR1% and ICG-based measurements provide complementary rather than interchangeable assessments of liver function. Histological and molecular analyses further demonstrated marked heterogeneity in fibrosis, steatosis, and hepatobiliary transporter expression across models, whereas transporter abundance alone did not consistently predict imaging-derived functional performance. Conclusions: Quantitative Gd-EOB-DTPA-enhanced T1 mapping provides a transporter-mediated imaging framework for evaluating hepatic functional reserve across mechanistically distinct liver injury models. As a normalized quantitative imaging biomarker, ΔR1% captures the integrated functional consequences of hepatobiliary transport dysfunction and complements established liver function tests. These findings support the translational potential of quantitative T1 mapping as a standardized, noninvasive approach for assessing liver functional reserve. Full article

Nova eruptions exhibit diverse photometric and spectroscopic properties traditionally classified using empirical light-curve morphology and spectral taxonomy. However, these observational classifications do not uniquely constrain the underlying eruption physics. This review examines the coupling between light-curve evolution, spectral development, ejecta dynamics, and multi-wavelength emission in classical and recurrent novae, with particular emphasis on the role of shocks and multi-phase outflows. Recent observations across optical, radio, X-ray, and gamma-ray wavelengths demonstrate that nova ejecta are intrinsically structured, anisotropic, and dynamically interacting systems, challenging the traditional interpretation of novae as spherically symmetric thermonuclear explosions. We synthesise observational and theoretical studies that link decline timescales, spectral transitions, expansion velocities, and high-energy emission to fundamental physical parameters, including white dwarf mass, accretion rate, ejecta geometry, and shock energetics. Using a compiled multi-parameter dataset of classical, recurrent, and symbiotic novae, we demonstrate that many commonly used observational diagnostics are intrinsically degenerate, with similar observable properties arising from different physical conditions. We argue that nova diversity is better understood within a continuous multi-dimensional parameter space rather than through purely empirical classifications. The implications of this framework for mass retention efficiency and the evolution of recurrent novae toward Type Ia supernova progenitors are discussed. Finally, we outline a predictive observational framework integrating photometric, spectroscopic, and high-energy diagnostics for future nova studies. Full article

The possibility of implementing intelligent irrigation has a number of undeniable advantages, mainly including the fact that the time can be determined and the volume of irrigation water can be adapted to specific plant types on a specific soil. A neural network has been trained to describe the dynamics of soil moisture based on the basic soil water retention curve (SWRC). It is able to take into account a wide range of input data, such as the specific surface area of the solid phase of soils, porosity, humidity, etc., for a given initial soil moisture profile. Preference is given to a recurrent neural network, since this type works well with sequential data and is able to take into account time dependence and solve the problem of decaying gradients of soil hydrophysical properties. The neural network processes the vector of incoming signs—humidity, temperature, volume of incoming/outgoing water, etc.—and connects them with the dynamics of humidity from sensors located at different depths. When modeling mass–salt transfer with different boundary and initial conditions, the dependence of moisture retention on the moisture conductivity function is used, which allows us to calculate how moisture with dissolved nutrients moves through the soil under the influence of pressure and concentration gradients. Since the SWRC is constructed as a function of directly measured data, it is easy to set it for each point of interest in the field and at each depth. During modeling, the soil is divided into elementary volumes (from 2–3 mm to 1 cm), and an array with data sets is compiled at each point. The research was conducted in a real hop plantation (the village of Opytny, Tsivilsky district, Republic of Chuvashia). The values of the soil moisture sensors at different depths, together with the data from the portable weather station, are sent to the input of the neural network. According to the minimum allowable humidity for hops, the model predicts situations when humidity reaches critical values and initiates watering. Thus, the implemented approach makes it possible to automate irrigation management, increase water use efficiency and ensure optimal conditions for plants. Full article

Oracle bone rejoining is central to oracle bone studies and digital cultural heritage curation, but many computer-assisted methods still rely on manually selected contour curves, candidate fracture edges, or local preprocessing. We introduce the Fast Siamese Diffusion Network for Oracle Bone Fragment Rejoining (FaSDiNet), a FasterNet-based Siamese framework with a latent-diffusion-based data augmentation module for full-fragment-image candidate screening and assisted rejoining of oracle bone fragments. FaSDiNet combines latent diffusion augmentation, a FasterNet-based Siamese feature encoder, and joint optimization of contrastive loss and binary cross-entropy loss to improve pairwise matching under limited training data. On the self-built OBF dataset, FaSDiNet achieves Top-1, Top-5, Top-10, and Top-15 recall values of 23.68%, 60.53%, 76.32%, and 84.21%, respectively. Among the evaluated OBF methods, its strongest comparative performance appears at broader candidate ranges, where it obtains the best Top-5, Top-10, and Top-15 recall values. On the public COBD dataset, FaSDiNet achieves Top-10 and Top-15 recall values of 93.8% and 96.9%, respectively, showing competitive candidate-retention performance at larger candidate ranges. These quantitative results indicate that FaSDiNet is especially effective for preserving truly rejoinable fragments within manageable ranked candidate lists, supporting efficient expert-assisted screening and offering a practical visual-computing workflow for oracle bone collation. Full article

Background and Objectives: Ventilation tube insertion (VTI) is the most commonly performed surgical procedure for otitis media with effusion (OME) in children. While the factors associated with tube extrusion have been investigated, their quantitative impact on the timing of extrusion remains insufficiently characterized. This study aimed to identify independent factors associated with ventilation tube extrusion time and to quantify the magnitude and direction of their effect using survival analysis methodology. Materials and Methods: This retrospective cohort study included 150 patients (262 ears) who underwent VTI with Shepard-type tubes for OME at a tertiary referral center between February 2019 and July 2025. Patient-level variables (age, sex, laterality, allergic rhinitis, secondhand smoke exposure, adenoidectomy, and tonsillectomy) were analyzed per patient (n = 150), while ear-specific variables (effusion type, history of previous VTI, and tube obstruction) were analyzed per ear (n = 262). Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent factors associated with extrusion time. Kaplan–Meier survival curves with log-rank tests were used to compare median extrusion times between groups. Results: The mean ventilation tube extrusion time was 280.38 ± 99.24 days (9.35 ± 3.30 months). Three independent factors significantly associated with shorter extrusion time were identified in multivariate analysis: tube obstruction during follow-up (HR = 2.629, 95% CI: 1.731–3.993, p < 0.001), history of previous VTI (HR = 2.292, 95% CI: 1.678–3.131, p < 0.001), and serous effusion type compared to glue (HR = 1.914, 95% CI: 1.455–2.517, p < 0.001). Age, sex, laterality, allergic rhinitis, secondhand smoke exposure, adenoidectomy, and tonsillectomy were not significantly associated with extrusion time. Conclusions: History of previous VTI, serous effusion type, and tube obstruction during follow-up were independently associated with shorter ventilation tube extrusion time. Notably, tube obstruction during follow-up, which has not been previously evaluated as a factor associated with extrusion time in survival analyses of tube retention, demonstrated the strongest independent effect on extrusion timing. These findings may assist clinicians in anticipating tube behavior and individualizing postoperative follow-up schedules. Full article

Introduction: The correct risk stratification is the key to achieving a low postoperative mortality after liver resection for HCC, including the evaluation of liver function and the presence of portal hypertension. The aim of this study was to evaluate the accuracy of Hepatic Venous-Portal pressure Gradients (HVPG), Indocyanine Green retention test (ICG-R15) and Liver Stiffness (LSM) in predicting the risk of post-hepatectomy liver failure and major postoperative complications in selected cirrhotic patients. Methods: A multicenter prospective study was designed, including consecutive cirrhotic patients undergoing liver resection for HCC. The predictive ability of HVPG, LSM and ICG-R15 was tested by evaluating the Area Under the ROC Curves. Results: Ninety-eight cirrhotic patients undergoing liver resection for HCC were included. Twelve patients (12.2%) developed at least one of the complications included within the composite endpoint. Three patients (3%) developed post-hepatectomy liver failure (PHLF) (one graded A and two graded C according to the International Study Group of Liver Surgery), five patients (5.1%) developed large ascites, five patients (5.1%) developed severe postoperative complications, two patients (2%) died during the hospital stay (PHLF). HVPG showed the higher AUC (0.778, 95% CI 0.641- 0.898; p < 0.001), followed by LSM (0.669, 95% CI 0.471–0.847; p = 0.097) and ICG-R15 (0.593, 95% CI 0.378–0.788; p = 0.615). Conclusions: In our cohort of selected HCC patients undergoing elective surgery, the predictive ability of HVPG on developing a composite endpoint including PHLF, in-hospital mortality, large postoperative ascites and major postoperative complications is higher than LSM and ICG-R15. Full article